95

Chapter 3

Health Effects of E‐Cigarette Use Among U.S. Youth and 

Young Adults

Introduction 97

Conclusions from Previous Surgeon General’s Reports 97

Health Effects of E‐Cigarette Use 100

Effects of Aerosol Inhalation by the E‐Cigarette User 100

Dose and Effects of Inhaling Aerosolized Nicotine 100

Aerosolized Nicotine and Cardiovascular Function 101

Aerosolized Nicotine and Dependence 102

Effects of Nicotine in Youth Users 104

Nicotine Exposure from Maternal Nicotine Consumption: Prenatal and Postnatal Health Outcomes 108

Summary 113

Effects of the Inhalation of Aerosol Constituents Other than Nicotine 114

Aerosolized Nicotine‐Related Compounds 114

Aerosolized Solvents 115

Aerosolized Flavorants 115

Aerosolized Adulterants 116

Summary 117

Effects of Toxicants Produced During Aerosolization 118

Summary 119

Effects Not Involving Inhalation of Aerosol by the E‐Cigarette User 119

Health Effects Attributable to Explosions and Fires Caused by E‐Cigarettes 119

Health Effects Caused by Ingestion of E‐Cigarette Liquids 119

Secondhand Exposure to the Constituents of E‐Cigarette Aerosol 120

Exposure to Nonusers 120

Movement of E‐Cigarette Aerosol 121

Exposure to E‐Cigarette Aerosol and Considerations of Dose 121

Health Effects of Secondhand Exposure to E‐Cigarette Aerosols 122

Evidence Summary 124

Conclusions 125

References 126

Health Effects of E-Cigarette Use Among U.S. Youth and Young Adults 97

E-Cigarette Use Among Youth and Young Adults

Introduction

This chapter focuses on the short‐term and poten‐ regarding harmful consequences of close contact with 

tial long‐term health effects related to the incidence and malfunctioning e‐cigarette devices and ingestion of the 

continued use of electronic cigarettes (e‐cigarettes) by nicotine‐containing liquids (e‐liquids) are also explored. 

youth and young adults. The sharp increase in the preva‐ This chapter examines available data on e‐cigarettes and 

lence of e‐cigarette use among youth and young adults, youth, reviews established human and animal data on 

especially from 2011 to 2015 (Centers for Disease Control harmful developmental effects of nicotine (prenatal and 

and Prevention [CDC] 2015, 2016), highlights the com‐ adolescent), and reviews data on e‐cigarettes among adults 

pelling need to learn more about this evolving class of when data on youth are not available. Of note, given the 

products. This chapter highlights the scientific litera‐ relatively recent emergence of e‐cigarettes, data are not 

ture that addresses potential adverse health effects caused yet available that address the long‐term health effects of 

by direct exposure to aerosolized nicotine, flavorants, use or exposure over several years compared with nonuse 

chemicals, and other particulates of e‐cigarettes; sec‐ or exposure to air free from secondhand tobacco smoke 

ondhand exposure to e‐cigarette aerosol; and exposure to and aerosol from e‐cigarettes; thus, the discussion is lim‐

the surface‐deposited aerosol contaminants. Literature ited in that regard.

Conclusions from Previous Surgeon General’s Reports

This chapter comprehensively reviews a new and 

emerging body of scientific evidence related to the use 

of e‐cigarettes by youth and young adults. The enormous 

knowledge base on tobacco smoking and human health 

is also relevant to this discussion. That literature, which 

has been accumulating for more than 50 years, provides 

incontrovertible evidence that smoking is a cause of dis‐

ease in almost every organ of the body (U.S. Department 

of Health and Human Services [USDHHS] 2004, 2014). 

Laboratory research has characterized the components 

of tobacco smoke and probed the mechanisms by which 

these constituents cause addiction and injury to cells, tis‐

sues, organs, and the developing fetus.

The evidence on the harmful consequences of nic‐

otine exposure in conventional cigarettes, including 

addiction, and other adverse effects, is particularly rel‐

evant to e‐cigarettes. Nicotine doses from e‐cigarettes 

vary tremendously depending on characteristics of the 

user (experience with smoking conventional cigarettes 

or e‐cigarettes), technical aspects of the e‐cigarette, and 

levels of nicotine in the e‐liquid. Although studies of nico‐

tine doses in youth and young adults are lacking, studies 

of adults have found delivery of nicotine from e‐cigarettes 

in doses ranging from negligible to as large as (Lopez 

et al. 2016; Vansickel and Eissenberg 2013; Spindle et al. 

2015; St. Helen et al. 2016) or larger than (Ramôa et al. 

2016) conventional cigarettes. Similarly, passive exposure 

to secondhand nicotine from e‐cigarettes is just as large 

(Flouris et al. 2013) or lower than (Czogala et al. 2014) 

conventional cigarettes.

The findings of scientific research on smoking 

and involuntary exposure to tobacco smoke have been 

reviewed thoroughly in the 32 reports on smoking and 

health produced by the Surgeon General to date (there is 

one report on smokeless tobacco) (Table 3.1). The land‐

mark first report was published in 1964 (U.S. Department 

of Health, Education, and Welfare [USDHEW] 1964), and 

the 50th‐anniversary report, released in January 2014, 

comprehensively covered multiple aspects of cigarette 

smoking and health and lengthened the list of diseases 

caused by smoking and involuntary exposure to tobacco 

smoke (USDHHS 2014). Other Surgeon General’s reports 

that are particularly relevant to the present report include 

reports on the health consequences of smoking and 

involuntary exposure to tobacco smoke (USDHHS 2004, 

2006), on the mechanisms by which smoking causes dis‐

ease (USDHHS 2010), and on the health consequences 

of smoking on youth and young adults (USDHHS 1994, 

2012). The Surgeon General’s reports on smoking and 

health have provided powerful conclusions on the dangers 

of nicotine. The 1988 report, released by Surgeon General 

C. Everett Koop, was the first to characterize smoking 

as addictive, and it identified nicotine as “...the drug in 

tobacco that causes addiction” (Appendix 3.1)1

1All appendixes and appendix tables that are cross‐referenced in this chapter are available only online at http://www.surgeongeneral.gov/

library/reports/

 (USDHHS 

1988, p. 9).
A Report of the Surgeon General

98 Chapter 3

Table 3.1 Relevant conclusions from previous Surgeon General’s reports on smoking and health

Report Year Conclusions

The Health 

Consequences of 

Smoking: Nicotine 

Addiction (USDHHS 

1988, p. 9)

1988 Major Conclusions

1. Cigarettes and other forms of tobacco are addicting.

2. Nicotine is the drug in tobacco that causes addiction.

3. The pharmacologic and behavioral processes that determine tobacco addiction are similar 

to those that determine addiction to drugs such as heroin and cocaine.

How Tobacco Smoke 

Causes Disease: The 

Biology and Behavioral 

Basis for SmokingAttributable Disease

(USDHHS 2010, p. 183)

2010 Chapter 4. Nicotine Addiction: Past and Present

1. Nicotine is the key chemical compound that causes and sustains the powerful addicting 

effects of commercial tobacco products.

2. The powerful addicting effects of commercial tobacco products are mediated by diverse 

actions of nicotine at multiple types of nicotinic receptors in the brain.

3. Evidence is suggestive that there may be psychosocial, biologic, and genetic determinants 

associated with different trajectories observed among population subgroups as they move 

from experimentation to heavy smoking.

4. Inherited genetic variation in genes such as CYP2A6 contributes to the differing patterns of 

smoking behavior and smoking cessation. 

5. Evidence is consistent that individual differences in smoking histories and severity of 

withdrawal symptoms are related to successful recovery from nicotine addiction.

Preventing Tobacco 

Use Among Youth and 

Young Adults (USDHHS 

2012, pp. 8, 460)

2012 Major Conclusions

1. Cigarette smoking by youth and young adults has immediate adverse health consequences, 

including addiction, and accelerates the development of chronic diseases across the full life 

course.

2. Prevention efforts must focus on both adolescents and young adults because among adults 

who become daily smokers, nearly all first use of cigarettes occurs by 18 years of age 

(88%), with 99% of first use by 26 years of age.

3. Advertising and promotional activities by tobacco companies have been shown to cause the 

onset and continuation of smoking among adolescents and young adults.

4. After years of steady progress, declines in the use of tobacco by youth and young adults 

have slowed for cigarette smoking and stalled for smokeless tobacco use.

5. Coordinated, multicomponent interventions that combine mass media campaigns, 

price increases including those that result from tax increases, school‐based policies and 

programs, and statewide or community‐wide changes in smokefree policies and norms are 

effective in reducing the initiation, prevalence, and intensity of smoking among youth and 

young adults. 

Chapter 4. Social, Environmental, Cognitive, and Genetic Influences on the Use of Tobacco 

Among Youth

1. Given their developmental stage, adolescents and young adults are uniquely susceptible to 

social and environmental influences to use tobacco.

2. Socioeconomic factors and educational attainment influence the development of youth 

smoking behavior. The adolescents most likely to begin to use tobacco and progress to 

regular use are those who have lower academic achievement.

3. The evidence is sufficient to conclude that there is a causal relationship between peer 

group social influences and the initiation and maintenance of smoking behaviors during 

adolescence.

4. Affective processes play an important role in youth smoking behavior, with a strong 

association between youth smoking and negative affect.

5. The evidence is suggestive that tobacco use is a heritable trait, more so for regular use 

than for onset. The expression of genetic risk for smoking among young people may be 

moderated by small‐group and larger social‐environmental factors.
Health Effects of E-Cigarette Use Among U.S. Youth and Young Adults 99

E-Cigarette Use Among Youth and Young Adults

Report Year Conclusions

The Health 

Consequences of 

Smoking—50 Years 

of Progress (USDHHS 

2014, p. 126)

2014 Chapter 5: Nicotine

1. The evidence is sufficient to infer that at high‐enough doses nicotine has acute toxicity.

2. The evidence is sufficient to infer that nicotine activates multiple biological pathways 

through which smoking increases risk for disease.

3. The evidence is sufficient to infer that nicotine exposure during fetal development, 

a critical window for brain development, has lasting adverse consequences for brain 

development.

4. The evidence is sufficient to infer that nicotine adversely affects maternal and fetal health 

during pregnancy, contributing to multiple adverse outcomes such as preterm delivery and 

stillbirth.

5. The evidence is suggestive that nicotine exposure during adolescence, a critical window for 

brain development, may have lasting adverse consequences for brain development.

6. The evidence is inadequate to infer the presence or absence of a causal relationship 

between exposure to nicotine and risk for cancer.

Note: USDHHS = U.S. Department of Health and Human Services.

Table 3.1 Continued

Subsequent reports expanded on the conclusions 

in the 1988 report related to nicotine—reaffirming that 

nicotine causes addiction, describing nicotine’s effects on 

key brain receptors (USDHHS 2010), and emphasizing 

that youth are more sensitive to nicotine than adults 

and can become dependent to nicotine much faster than 

adults (USDHHS 2012). This is of particular concern in 

the context of e‐cigarettes because blood nicotine levels 

in e‐cigarette users have been reported as being compa‐

rable to or higher than levels in smokers of conventional 

cigarettes (Lopez et al. 2016; Spindle et al. 2015), and 

serum cotinine (a nicotine metabolite) levels have been 

reported as being equal to that found in conventional ciga‐

rette users (Etter 2016; Marsot and Simon 2016). Because 

of their sensitivity to nicotine and subsequent addiction, 

about 3  out of 14 young smokers end up smoking into 

adulthood, even if they intend to quit after a few years; 

among youth who continue to smoke as adults, one‐

half will die prematurely from smoking (Peto et al. 1994; 

CDC 1996; Hahn et al. 2002; Doll et al. 2004). Surgeon 

General’s reports have also emphasized the critical role 

of environmental determinants of tobacco use, including 

the causal roles of the tobacco industry’s advertising and 

promotional activities and of the peer social environment 

(USDHHS 2012).

The review documented the broad biological activity of 

nicotine, which can activate multiple biological path‐

ways, and the adverse effects of nicotine exposure during 

pregnancy on fetal development and during adolescence 

on brain development. Of concern with regard to cur‐

rent trends in e‐cigarette use among youth and young 

adults, the evidence suggests that exposure to nicotine 

during this period of life may have lasting deleterious con‐

sequences for brain development, including detrimental 

effects on cognition (USDHHS 2014).

The 2014 Surgeon General’s report included a 

chapter that addressed the numerous adverse conse‐

quences of nicotine other than addiction (USDHHS 2014). 

Finally, the aerosol from e‐cigarettes may include 

other components that have been addressed in previous 

Surgeon General’s reports, such as tobacco‐specific nitro‐

samines (TSNAs), acrolein, and formaldehyde (USDHEW 

1979; USDHHS 2010). Aerosols generated with vapor‐

izers contain up to 31 compounds, including nicotine, 

nicotyrine, formaldehyde, acetaldehyde glycidol, acro‐

lein, acetol, and diacetyl (Sleiman et al. 2016). Glycidol 

is a probable carcinogen not previously identified in the 

vapor, and acrolein is a powerful irritant (Sleiman et al. 

2016). Although these constituents have been identified in 

e‐cigarette aerosol, current evidence is unclear on whether 

typical user dosages achieve levels as high as conventional 

cigarettes, or at harmful or potentially harmful levels. 

More information will be available in the coming years 

as e‐cigarette manufacturers begin reporting harmful or 

potential harmful constituents in compliance with the 

Tobacco Control Act.
A Report of the Surgeon General

100 Chapter 3

Health Effects of E‐Cigarette Use

The potential adverse health effects for youth who 

inhale e‐cigarette aerosol include those on the body from 

acute administration of nicotine, flavorants, chemicals, 

other particulates, and additional effects, such as (1) nico‐

tine addiction; (2) developmental effects on the brain from 

nicotine exposure, which may have implications for cog‐

nition, attention, and mood; (3) e‐cigarette influence ini‐

tiating or supporting the use of conventional cigarettes 

and dual use of conventional cigarettes and e‐cigarettes; 

(4)  e‐cigarette influence on subsequent illicit drug use;

(5) e‐cigarette effects on psychosocial health, particularly 

among youth with one or more comorbid mental health 

disorders; and (6) battery explosion and accidental overdose 

of nicotine.

Effects of Aerosol Inhalation by the 

E‐Cigarette User

Determining the potential health effects of inhaling 

e‐cigarette aerosol is challenging due to the number of pos‐

sible combinations of customizable options (Seidenberg 

et al. 2016), including battery power, nicotine concentra‐

tion, e‐liquids (Goniewicz et al. 2015; Buettner‐Schmidt 

et al. 2016), and use behaviors and puff topography (Dawkins 

et al. 2016; Lopez et al. 2016). The amount of nicotine, fla‐

vorants, and other e‐liquid constituents in e‐cigarettes 

available for consumers to purchase varies widely, and the 

aerosolized constituents delivered vary by the type and 

voltage of the e‐cigarette device being used (Cobb et al. 

2015). Studies of commercial products have shown that 

e‐liquids can contain as little as 0 milligrams/milliliter 

(mg/mL) to as much as 36.6 mg/mL of nicotine (Goniewicz 

et al. 2015); can be mislabeled (Peace et al. 2016); can vary 

by propylene glycol (PG)/vegetable glycerin (VG) ratio; and 

can contain one or more of several thousand available fla‐

vorants (Zhu et al. 2014b). Some liquids intended for use in 

e‐cigarettes contain adulterants not named on ingredient 

lists (Varlet et al. 2015), and under at least some user con‐

ditions, the aerosolization process, which involves heating, 

produces additional toxicants that may present health risks 

(Talih et al. 2015). The sections that follow comprehen‐

sively cover the effects of inhaling aerosolized nicotine and 

then consider what is known about solvents (i.e., PG and 

VG, flavorants, and other chemicals) added to e‐cigarettes, 

adulterants in e‐liquids formed in the nicotine extraction 

process (e.g., N‐nitrosonornicotine), and toxicants formed 

during the heating and aerosolization process (e.g., acro‐

lein and formaldehyde) (Sleiman et al. 2016).

Dose and Effects of Inhaling Aerosolized Nicotine

Nicotine addiction via e‐cigarette use is a primary 

public health concern due to the exponential growth in 

e‐cigarette use among youth. The potential for widespread 

nicotine addiction among youth is high, as are the harmful 

consequences of nicotine on fetal development and the 

developing adolescent brain (USDHHS 2014). Nicotine, a 

psychomotor stimulant drug, is the primary psychoactive 

and addictive constituent in the smoke of conventional 

cigarettes and an important determinant in maintaining 

smoking dependence (e.g., USDHHS 2014). E‐liquids 

typically contain nicotine, although in more widely vari‐

able concentrations than those found in conventional 

cigarettes (Trehy et al. 2011; Cameron et al. 2014; Cheng 

2014; Goniewicz et al. 2015; Marsot and Simon 2016). The 

concentration of liquid nicotine is only one factor that 

influences the amount of aerosolized nicotine available 

for inhalation (Lopez et al. 2016); other factors include 

the power of the device being used (e.g., battery voltage, 

heater resistance) and user behavior (e.g., puff duration, 

interpuff interval) (Shihadeh and Eissenberg 2015; Talih 

et al. 2016; Etter 2016). The interplay of these factors may 

help to explain the variability in plasma nicotine concen‐

tration when adults use e‐cigarettes under controlled con‐

ditions which can be higher (Ramôa et al. 2016), lower 

(Bullen et al. 2010; Vansickel et al. 2010, 2012; Farsalinos 

et al. 2014b; Nides et al. 2014; Oncken et al. 2015; Yan 

and D’Ruiz 2015), or similar to those obtained by smoking 

conventional cigarettes (Vansickel and Eissenberg 2013; 

Spindle et al. 2015; St. Helen et al. 2016; see Figure 3.1). 

Generalization across studies is difficult due to variations 

in devices, e‐liquids, and e‐cigarette use behavior within 

the study sample. As demonstrated in Figure 3.1, in studies 

where a variety of products were used under similar labo‐

ratory conditions (i.e., blood sampling before and imme‐

diately after a 10‐puff episode), there was wide variability 

in nicotine delivery between devices, with “cigalike” prod‐

ucts (cigarette‐like products) delivering less nicotine than 

“tank” products (Farsalinos et al. 2014b; Yan and D’Ruiz 

2015), and low‐resistance, dual‐coil “cartomizer” prod‐

ucts having the capacity to deliver less or more nicotine 

than a conventional cigarette, depending on the concen‐

tration of liquid nicotine (Ramôa et al. 2016).

When the device type and liquid dose were held con‐

stant in a controlled session in one study, plasma nico‐

tine concentrations (in this case in nanograms [ng]/mL) 

varied considerably across participants (0.8 to 8.5 ng/mL) 

(Nides et al. 2014). This variation was likely attributable 

to the manner in which the users puffed when using 
Health Effects of E-Cigarette Use Among U.S. Youth and Young Adults 101

E-Cigarette Use Among Youth and Young Adults

e‐cigarettes, or that person’s “puff topography,” which 

includes the number of puffs, the intake volume and dura‐

tion, the interpuff interval, and the flow rate (Zacny and 

Stitzer 1988; Blank et al. 2009).

Available data suggest that puff durations among 

adult cigarette smokers who are new e‐cigarette users 

are comparable to those observed with conventional cig‐

arettes (at least about 2 seconds [sec]) (Farsalinos et al. 

2013b; Hua et  al. 2013; Norton et  al. 2014). However, 

puff durations during e‐cigarette use among experienced 

e‐cigarette users may be twice as long (~4 sec) (Farsalinos 

et al. 2013b; Hua et al. 2013; Spindle et al. 2015) as puff 

duration during conventional cigarette use. Puff duration 

is directly related to the nicotine content of the e‐cigarette 

aerosol (i.e., the yield or dose) (Talih et  al. 2016), sug‐

gesting that smokers of conventional cigarettes who switch 

to e‐cigarettes may increase the duration of their puffs 

when using the new product in an attempt to extract more 

nicotine. Research also suggests that cigarette smokers 

may learn to alter other aspects of their puffing behavior 

when using an e‐cigarette (Spindle et al. 2015). Relative 

to smokers of conventional cigarettes (Kleykamp et  al. 

2008), experienced e‐cigarette users were found to have 

puff volumes that were significantly higher (101.4 mL vs. 

51.3 mL) and puff flow rates that were significantly lower 

(24.2 mL/sec vs. 37.9 mL/sec) (Spindle et al. 2015). In a 

different study, adult cigarette smokers who had never 

used e‐cigarettes but switched to e‐cigarettes showed sig‐

nificantly increased puff durations and decreased puff flow 

rates within 1 week (Lee et al. 2015). Elsewhere, adult cig‐

arette smokers given an e‐cigarette appeared to show an 

enhanced ability to extract nicotine from their device after 

4 weeks of use (Hajek et al. 2015). Thus, the health effects 

of aerosolized nicotine in e‐cigarette users may depend on 

a variety of factors, including the e‐liquid used, the user’s 

behavior, and the user’s experience with the product.

Aerosolized Nicotine and Cardiovascular Function

Smoking is a major cause of death from cardiovas‐

cular disease (USDHHS 2014), and exposure to nicotine 

has been identified as a potential initiating factor in the 

atherogenic process (Lee et al. 2011; Santanam et al. 2012; 

Benowitz and Burbank 2016). Acute administration of 

nicotine causes a variety of well‐characterized, dose‐ and 

route‐dependent effects in adults, including cardiovascular 

effects, such as increases in heart rate and blood pressure 

(BP) and greater cardiac output, leading to an increase 

in myocardial oxygen demand (Rosenberg et  al. 1980; 

USDHHS 2014). Reports from cell biology and animal 

studies have established biologic plausibility between nic‐

otine alone and negative cardiovascular effects (Hanna 

2006; Santanam et  al. 2012). These studies have shown 

that nicotine induces the production of various inflam‐

matory mediators involved with atherosclerotic patho‐

genesis (Lau and Baldus 2006), and that at the cellular 

level, nicotine induces C‐reactive protein (CRP) expres‐

sion in macrophages that contribute pro‐inflammatory 

and pro‐atherosclerotic effects (Mao et al. 2012).

Long‐term studies on the safety of nicotine‐only 

exposure (e.g., as with using e‐cigarettes rather than 

smoking conventional cigarettes) among youth have not 

been conducted, and little is known about the cardiovas‐

cular effects of e‐cigarette use among adults. However, 

when e‐cigarettes are accompanied by a measurable 

increase in plasma nicotine concentration, it increases 

heart rate (Vansickel et al. 2012; Vansickel and Eissenberg 

2013; Nides et al. 2014; Yan and D’Ruiz 2015), and dia‐

stolic BP rises.

Given the paucity of long‐term data on the impact of 

e‐cigarette smoking in relation to cardiovascular disease, 

other nicotine products offer a useful analogy. A meta‐

analysis reported that replacing the consumption of con‐

ventional cigarettes with nicotine replacement therapy 

(NRT) reduces cardiovascular risk among former smokers 

without significant adverse consequences (compared with 

current smokers) (Greenland et  al. 1998; Moore et  al. 

2009). However, most NRT use is temporary (<26 months), 

and the adverse consequences of longer term NRT therapy 

are unknown.

Elsewhere, investigators examined the relationship 

between the use of Swedish‐type moist snuff (or “snus”), 

which contains high levels of nicotine and low levels of 

TSNAs, and the incidence of acute myocardial infarction 

among men with a mean age of 35 years who had never 

smoked cigarettes. The researchers, who pooled data from 

eight prospective cohort studies, found no support for 

any association between the use of snus and the develop‐

ment of acute myocardial infarction (Hansson et al. 2012), 

regardless of timing, intensity, duration, or period of use 

among the men who were followed for 4–29 years.

In summary, despite overwhelming epidemiologic 

evidence linking the use of conventional cigarettes with 

cardiovascular disease, the precise components of cig‐

arette smoke responsible for this relationship and the 

mechanisms by which they exert their effects have not yet 

been fully explained (Hanna 2006). For e‐cigarettes, bio‐

logical data support a potential association with cardio‐

vascular disease, and short‐term use of these products is 

accompanied by a measurable increase in plasma nicotine 

concentrations in adults as well as increases in heart rate 

and blood pressure. Much more research is needed, but the 

limited data available suggest the typical cardiovascular 

effects exerted by nicotine are also exerted by e‐cigarettes 

(Benowitz and Burbank 2016; Bhatnagar 2016).
A Report of the Surgeon General

102 Chapter 3

Aerosolized Nicotine and Dependence

Although a great deal is known about self‐

administration of nicotine and the development of nicotine 

dependence among adults (USDHHS 2014) and youth (Colby 

et al. 2000; USDHHS 2012; O’Loughlin et al. 2014; Yuan et al. 

2015), more research is needed on nicotine dependence in 

youth and young adults as a result of using e‐cigarettes. 

Nicotine dependence, also referred to as nicotine addic‐

tion (USDHHS 2010) or tobacco use disorder (American 

Psychiatric Association [APA] 2013), is defined as a neu‐

robiological adaptation to repeated drug exposure that is 

manifested behaviorally by highly controlled or compulsive 

use; psychoactive effects such as tolerance, physical depen‐

dence, and pleasant effect; and nicotine‐reinforced behavior, 

including an inability to quit despite harmful effects, a 

desire to quit, and repeated cessation attempts (USDHHS 

1988; APA 2013). In tobacco‐dependent users of conven‐

tional cigarettes, a predictable consequence of short‐term 

abstinence (e.g., for more than a few hours) is the onset 

of withdrawal symptoms indicated by self‐reported behav‐

ioral, cognitive, and physiological symptoms and by clinical 

signs (USDHHS 2010). Subjective withdrawal symptoms 

are manifested by affective disturbance, including irrita‐

bility and anger, anxiety, and depressed mood. The behav‐

ioral symptoms include restlessness, sleep disturbance, and 

increased appetite. Cognitive disturbances usually center 

on difficulty in concentrating (USDHHS 2010).

Early studies of conventional cigarette smokers 

using e‐cigarettes reported poor nicotine delivery with 

little to no increase in blood nicotine levels after puffing 

(Eissenberg 2010; Vansickel et al. 2010). Later studies 

reported that the effect on serum cotinine levels among 

new e‐cigarette users can be similar to that generated by 

conventional cigarettes (Flouris et al. 2013; Lopez et al. 

2016). Studies examining this discrepancy found that 

e‐cigarette users require longer puffs to deliver equivalent 

nicotine doses (Lee et al. 2015), and within a week, inex‐

perienced e‐cigarette users adjust their puffing patterns 

after switching (Hua et al. 2013b; Lee et al. 2015; Talih 

et al. 2015).

In more experienced e‐cigarette users, blood nico‐

tine levels appear to be influenced by puffing patterns, 

such as puff length. Volume and frequency and plasma 

nicotine levels ranging from 2.50 to 13.4 ng/mL have 

been observed after 10 puffs of an e‐cigarette (Dawkins 

and Corcoran 2014). Dawkins and colleagues (2016) used 

24  mg/mL nicotine strength liquid and observed high 

blood nicotine levels that were achieved very quickly, 

matching and even exceeding those reported in conven‐

tional cigarette smokers. St. Helen and colleagues (2016) 

conducted a similar study and reported that e‐cigarettes 

can deliver levels of nicotine that are comparable to or 

higher than conventional cigarettes. Finally, Etter (2016) 

reported cotinine levels among experienced e‐cigarette 

users similar to levels usually observed in conven‐

tional cigarette smokers. Figure 3.1 and Table A3.1‐1 in 

Appendix  3.1 summarize studies on aerosolized nico‐

tine from e‐cigarettes and dependence using dependency 

criteria.

The ability of e‐cigarettes to deliver comparable or 

higher amounts of nicotine compared to conventional 

cigarettes raises concerns about e‐cigarette use gener‐

ating nicotine dependence among young people (Dawkins 

et al. 2016; Etter 2016; St. Helen et al. 2016). The reported 

blood levels of nicotine, or cotinine, in e‐cigarette users 

is likely to cause physiological changes in nicotinic ace‐

tylcholine receptors in the brain that would sustain nico‐

tine addiction (Kandel and Kandel 2014; Yuan et al. 2015). 

This is particularly concerning for adolescents and young 

adults, given that early exposure to nicotine increases the 

severity of future nicotine dependence (St. Helen et al. 

2016; USDHHS 2014).

Symptoms of nicotine dependence can occur soon 

after the initiation of conventional smoking, and even 

before established use, among adolescents and young 

adults (DiFranza et al. 2002; O’Loughlin et al. 2003; 

Dierker et al. 2007; Ramôa et al. 2016). Furthermore, 

some adolescents have reported nicotine dependence 

symptoms while using tobacco as little as 1–3 days per 

month (Rose et al. 2010). Using the National Comorbidity 

Survey‐Adolescent dataset, Dierker and colleagues (2012) 

reported that nicotine dependence in adolescents was 

likely to occur within 1 year of the initiation of weekly or 

daily smoking, regardless of sociodemographic variables. 

Importantly, when smoking onset began at a younger 

age, the transition to weekly and daily smoking was more 

rapid, indicating a youthful neurobiological sensitivity to 

nicotine (Dierker et al. 2012). Zhan and colleagues (2012) 

found that symptoms of nicotine dependence could be 

detected among teenagers before they had smoked even 

100 cigarettes.

Because few validated measures exist for assessing 

dependence on e‐cigarette use, some researchers have 

adapted those originally developed to measure dependence 

in smokers of conventional cigarettes. Among adults, 

scores on these measures have been consistently lower 

in e‐cigarette users than in smokers of conventional ciga‐

rettes (Farsalinos et al. 2013a; Etter and Eissenberg 2015; 

Foulds et al. 2015). Still, scores for e‐cigarette dependence 

among former cigarette smokers were positively associ‐

ated with the nicotine concentration of the e‐cigarette 

liquid and the type of device used (Etter 2015; Etter and 

Eissenberg 2015; Foulds et  al. 2015). Research in this 

area is challenging to interpret because measurement of 

youth e‐cigarette dependence has not been standardized
Health Effects of E-Cigarette Use Among U.S. Youth and Young Adults 103

E-Cigarette Use Among Youth and Young Adults

Figure 3.1 Plasma nicotine concentration from different human laboratory studies and four different products with 

blood sampled before and immediately after a 10‐puff bout with the products

Source: Vansickel et al. (2010); Farsalinos et al. (2014b); Yan and D’Ruiz (2015); and Ramôa et al. (2016).

Notes: Data for conventional cigarettes are from 32 tobacco cigarette smokers using their usual brand of cigarette (Vansickel et al. 2010). 

E‐cigarette A is a cigalike called “blu” loaded with two different concentrations of liquid nicotine (16 or 24 mg/mL, both containing 20% 

propylene glycol and 50% vegetable glycerin). Data are from 23 smokers of tobacco cigarettes with 7 days of experience with the e‐cigarette 

product (Yan and D’Ruiz 2015). E‐cigarette B is a cigalike called “V2cigs”, and E‐cigarette C is a “tank” product called “EVIC” with an “Evod” 

heating element; both were loaded with an 18 mg/mL liquid containing 34% propylene glycol and 66% vegetable glycerin. Data are from 23 

experienced users of e‐cigarettes (Farsalinos et al. 2014b). E‐cigarette D uses a 3.3‐volt “Ego” battery fitted with a 1.5‐Ohm dual coil carto‐

mizer (“Smoktech”) and filled with ~1 mL of a 70% propylene glycol, 30% vegetable glycerin liquid that varied by liquid nicotine concentra‐

tion (0, 8, 18, or 36 mg/mL). Data are from 16 experienced users of e‐cigarettes (Ramôa et al. 2016).
A Report of the Surgeon General

104 Chapter 3

(Continued from last paragraph on page 102.)

and there is a wide variation in device/e‐liquid combina‐

tions, which allow for adjustable nicotine delivery among

study participants. Regardless, among 766 adults, who

were daily users of e‐cigarettes (with nicotine) and who

were either former cigarette smokers (83%) or current

cigarette smokers (17%), 30.7% indicated that they would

likely be unable to stop using e‐cigarettes, 28.2% that they

would find it “very difficult” or “impossible” to stop using

e‐cigarettes, and 27.5% that they were unable to stop

e‐cigarette use (Etter and Eissenberg 2015). However, it

is important to note that e‐cigarettes were less addictive

than conventional cigarettes in this sample (Etter and

Eissenberg 2015).

In summary, the addictive liability of e‐cigarettes 

has the potential to be at least equivalent to that of con‐

ventional cigarettes, given nicotine dose levels produced 

by these products, particularly among experienced users 

operating new‐generation devices (Ramôa et al. 2016). 

More generally, the delivery of nicotine in sufficient doses 

and blood concentration would be expected to produce 

and maintain dependence in e‐cigarette users. Further 

work would be useful to determine the natural course 

and history of e‐cigarette use among smokers of conven‐

tional cigarettes, former smokers, and never smokers and 

to more accurately determine the nicotine addiction lia‐

bility of e‐cigarette use. Unfortunately, these issues have 

not been explored in adolescents, although the prevalence 

of e‐cigarette use has increased considerably in that popu‐

lation since 2011 (see Chapter 2).

Effects of Nicotine in Youth Users

Nicotine is the prime psychoactive substance in con‐

ventional cigarettes (Yuan et al. 2015), and given that the 

developing adolescent brain is immature and vulnerable 

to neurobiological insults (Bernheim et  al. 2013; Lydon 

et al. 2014), it is important to understand how nicotine 

delivered by e‐cigarette use affects adolescent brain devel‐

opment and how responses to nicotine in adolescents 

differ from those seen in adults. Substantial evidence sug‐

gests that nicotine can negatively influence both adoles‐

cent and prenatal brain development (USDHHS 2014). 

For example, Weiss and colleagues (2008) reported a 

strong mechanistic link among early nicotine exposure 

(younger than 16 years of age), common genes related to 

the severity of nicotine addiction (CHRNA5‐A3‐B4 hap‐

lotypes), and adult nicotine addiction in three indepen‐

dent populations of European origins. Although much of 

the literature on nicotine addiction arises from studies 

of nicotine exposure among adults, and with combus‐

tible tobacco products (see Table A3.1‐2 in Appendix 3.1), 

there is a growing body of biological mechanistic litera‐

ture from animal studies that model the effects of nicotine 

in doses equivalent to those for humans (see Table A3.1‐3 

in Appendix 3.1). These animal and human studies, taken 

together with studies of rising e‐cigarette prevalence in 

youth (see Chapter 2), point to an age‐dependent suscep‐

tibility to nicotine as a neurobiological insult.

Limited direct human experimental data exist on 

the effects of nicotine exposure from e‐cigarettes on the 

developing adolescent brain, but experimental laboratory 

data have been found to be relevant in animal models to 

contextualize effects in humans (Stevens and Vaccarino 

2015). Even if the full complexity of human brain develop‐

ment and behavioral function during adolescence cannot 

be completely modeled in other species, the similarities 

across adolescents of different species support the use of 

animal models of adolescence when examining neural and 

environmental contributors to adolescent‐characteristic 

functioning (Spear 2010).

Animal studies provide an effective method to 

examine the persistent effects of prenatal, child, and ado‐

lescent nicotine exposure, in addition to human epide‐

miologic data. When considering an epidemiologic causal 

argument of exposure (risk factor) to health outcome (dis‐

ease), one should note that animal models lend biolog‐

ical plausibility when experimentation with humans is not 

possible (or ethical) (Rothman et al. 2008). Furthermore, 

animal studies offer significant advantages compared to 

human studies—with the ability to control for many con‐

founding factors, to limit nicotine exposure to differing 

levels of physical and neural development—and are piv‐

otal for understanding the neural substrates associated 

with adolescence. The validity of any causal argument 

when examining animal models requires careful consider‐

ation, and yet in combination with epidemiologic data—

such as prevalence, incidence, and strength of association 

between exposure and outcome—a causal argument can 

be constructed with literature from animal models rep‐

resenting biologic plausibility. Using a variety of study 

designs and research paradigms including humans and 

animals, research in this area provides evidence for neu‐

roteratogenic and neurotoxic effects on the developing 

adolescent brain (Lydon et al. 2014; England et al. 2015).

The brain undergoes significant neurobiological 

development during adolescence and young adulthood, 

which are critical periods of sensitivity to neurobiolog‐

ical insults (such as nicotine) and experience‐induced 

plasticity (Spear 2000; Dahl 2004; Gulley and Juraska 

2013). Although maturation occurs in different regions of 

the brain at different rates, a similar progression occurs 

in all areas characterized by a rapid formation of syn‐

aptic connections in early childhood, followed by a loss 

of redundant or unnecessary synapses (called pruning) 

and the formation of myelin. Myelination is the process 

by which a fatty layer, called myelin, accumulates around 
Health Effects of E-Cigarette Use Among U.S. Youth and Young Adults 105

E-Cigarette Use Among Youth and Young Adults

nerve cells (neurons). Because of myelin, nerve cells can 

transmit information faster, allowing for more complex 

brain processes. Pruning allows for more focused con‐

centration, and myelination allows for faster electrical 

and neural signaling; both allow for more efficient cog‐

nitive processing. During adolescence and into young 

adulthood, myelination occurs rapidly in the frontal lobe, 

a place in the brain that controls executive functioning, 

reasoning, decision‐making skills, self‐discipline, and 

impulse control. Plasticity refers to the current under‐

standing that the brain continues to change throughout 

life, not only because of normal, maturational neural 

growth and development but also because of changes in 

environmental neurobiological exposures (such as nico‐

tine), injuries, behaviors, thinking, and emotions (Mills 

and Tamnes 2014).

Across species, and in humans, adolescence is a key 

period of increased plasticity and rapid growth of brain 

circuits that regulate social, emotional, and motivational 

processes and decision making (Spear 2000, 2011; Nelson 

et al. 2005; Ernst and Fudge 2009; Counotte et al. 2011). 

The prefrontal cortex, which is involved in higher level 

regulatory control of complex behaviors (such as plan‐

ning, impulse control, and working memory), continues 

normal structural and functional development into young 

adulthood, to about 25 years of age (Giedd and Rapoport 

2010; Somerville and Casey 2010). Because of the immatu‐

rity and rapid growth of the prefrontal cortex, adolescents 

and young adults normally exhibit moody, risk‐taking, 

and unpredictable impulsive behaviors. The combina‐

tion of delayed maturation of frontal cognitive control 

and increased reactivity of subcortical reward‐related 

and emotion‐processing systems may lead to increased 

risk‐taking behavior and a greater susceptibility to initi‐

ating substance use and the development of dependence 

(Steinberg 2008; Ernst and Fudge 2009; Counotte et al. 

2011; Spear 2011). Thus, myelination is vitally important 

to the healthy functioning of the central nervous system, 

and any exposure that significantly interferes with the 

myelination process can cause mild‐to‐severe cognitive 

and learning problems (Brady et al. 2012).

Brain development in juvenile rodents has been 

reported to display patterns that resemble those of human 

beings, suggesting that the rodent model might be rel‐

evant to studying the neurobiological underpinnings 

of brain maturation in teenagers (Spear 2000). Studies 

across species have revealed unique characteristics of 

adolescent nonhuman brain structure, mechanisms, and 

function that provide biological plausibility to the hypoth‐

esis that human adolescents are particularly vulnerable to 

nicotine uptake (O’Loughlin et al. 2015; Yuan et al. 2015). 

There is evidence for rapid growth of gray matter, fol‐

lowed by activity‐dependent synaptic pruning (the process 

of synapse elimination that occurs between early child‐

hood and the onset of puberty) and increasing myelina‐

tion throughout the brain (Casey et al. 2005; Lenroot and 

Giedd 2006; Giedd and Rapoport 2010; Counotte et  al. 

2011).

Nicotine has more significant and durable damaging 

effects on adolescent brains compared to adult brains, 

the former suffering more harmful effects. Preclinical 

animal studies have shown that in rodent models, nico‐

tinic acetylcholine receptor (nAChR) signaling is still 

actively changing during adolescence, with higher expres‐

sion and functional activity of nAChRs in the forebrain 

of adolescent rodents compared to their adult counter‐

parts (Britton et al. 2007; Kota et al. 2007; Doura et al. 

2008). Furthermore, in rodent models, nicotine actu‐

ally enhances neuronal activity in several reward‐related 

regions and does so more robustly in adolescents than in 

adults (Schochet et al. 2005; Shram et al. 2007; Dao et al. 

2011). This increased sensitivity to nicotine in the reward 

pathways of adolescent rats is associated with enhanced 

behavioral responses, such as strengthening the stimulus‐

response reward for administration of nicotine. In condi‐

tioned place‐preference tests—where reward is measured 

by the amount of time animals spend in an environment 

where they receive nicotine compared to an environment 

where nicotine is not administered—adolescent rodents 

have shown an increased sensitivity to the rewarding 

effects of nicotine at very low doses (0.03 mg/kg) (Vastola 

et  al. 2002; Belluzzi et  al. 2004; Brielmaier et  al. 2007; 

Kota et  al. 2007; Natarajan et  al. 2011) and exhib‐

ited a unique vulnerability to oral self‐administration 

during the early‐adolescent period (Adriani et  al. 2002). 

Adolescent rodents also have shown higher levels of nic‐

otine self‐administration than adults (Levin et  al. 2003; 

Chen et al. 2007; Natividad et al. 2013), decreased sensi‐

tivity to the aversive effects of nicotine (Adriani et al. 2002; 

Shram et al. 2006; Torres et al. 2008), and less prominent 

withdrawal symptoms following chronic nicotine expo‐

sure (O’Dell et  al. 2006). This characteristic in rodent 

models of increased positive and decreased negative short‐

term effects of nicotine during adolescence (versus adult‐

hood) highlights the possibility that human adolescents 

might be particularly vulnerable to developing depen‐

dency to and continuing to use e‐cigarettes. These bio‐

logical mechanisms are of great public health importance 

as exposure to nicotine grows among nonsmoking youth 

through the increasing prevalence of e‐cigarette use.

Beyond their unique vulnerability to nicotine use, 

and thus smoking uptake, human adolescents may be par‐

ticularly vulnerable to the detrimental consequences of 

nicotine exposure, including an increase in drug‐seeking 

behaviors (Kandel and Kandel 2014), deficits in attention 

and cognition, and mood disorders (Yuan et al. 2015). In 
A Report of the Surgeon General

106 Chapter 3

animal models, chronic nicotine exposure during adoles‐

cence has been shown to produce long‐lasting, unique 

effects that are not observed in mature adult animals. 

Moreover, animal models have provided substantial evi‐

dence that the limbic system—which controls cognition, 

emotion, and drug‐reward—is actively maturing during 

adolescence and during this age is vulnerable to long‐

term modification by nicotine.

Reward‐Seeking Behaviors. A very strong argument 

can be made about the association between adolescent expo‐

sure to nicotine by smoking conventional cigarettes and 

the subsequent onset of using other dependence‐producing 

substances. Strong, temporal, and dose‐dependent associa‐

tions have been reported (Isensee et al. 2003; John et al. 

2004b; Bronisch et al. 2008; Kandel and Kandel 2015), and 

a plausible biological mechanism (via rodent and human 

modeling) suggests that long‐term changes in the neural 

reward system take place as a result of adolescent smoking 

(Lewinsohn et al. 1999; Huang et al. 2013; Kandel and 

Kandel 2014). Adolescent smokers of conventional ciga‐

rettes have disproportionately high rates of comorbid sub‐

stance abuse (Kandel et al. 1992; Lai et al. 2000; Hanna et al. 

2001), and longitudinal studies have suggested that early 

adolescent smoking may be a starting point or “gateway” for 

substance abuse later in life (Kandel et al. 1992; Lewinsohn 

et al. 1999; Wagner and Anthony 2002; Brook et al. 2007), 

with this effect more likely for persons with attention 

deficit hyperactivity disorder (ADHD) (Biederman et al. 

2006; Wilens et al. 2008). Although factors such as genetic 

comorbidity, innate propensity for risk taking, and social 

influences may underlie these findings (Lindsay and Rainey 

1997; Smith et al. 2015), both human neuroimaging and 

animal studies suggest a neurobiological mechanism also 

plays a role. In addition, behavioral studies in adolescent 

and young adult smokers have revealed an increased pro‐

pensity for risk taking, both generally and in the presence of 

peers, and neuroimaging studies have shown altered frontal 

neural activation during a risk‐taking task as compared 

with nonsmokers (Lejuez et al. 2005; Cavalca et al. 2013; 

Galvan et al. 2013). Rubinstein and colleagues (2011b) used 

neuroimaging to show decreased brain response to a nat‐

ural reinforcer (pleasurable food cues) in adolescent light 

smokers (1–5 cigarettes per day), with their results high‐

lighting the possibility of neural alterations consistent with 

nicotine dependence and altered brain response to reward 

even in adolescent low‐level smokers.

Nicotine exposure in rodents at an age of physical 

development corresponding to human adolescence has 

been found to increase the reinforcing effects of other 

drugs of abuse, including cocaine, methamphetamine, 

and alcohol, without having a major impact on responding 

for other rewards, thus providing further evidence in sup‐

port of nicotine as an initiation toward other substance 

use and abuse (McQuown et al. 2007; Dao et al. 2011; 

Dickson et al. 2014; Pipkin et al. 2014; Kandel and Kandel 

2014). In several rodent studies, treatment with very low 

doses of nicotine for a few days during early adolescence, 

but not in late adolescence or adulthood, produced lasting 

changes in D2 and D3 dopamine receptors and in the self‐

administration of other abused drugs (McQuown et al. 

2007; Dao et al. 2011; Mojica et al. 2014). Nicotine expo‐

sure in adolescent rats also induced rapid and long‐lasting 

dendritic remodeling in the nucleus accumbens shell, a 

critical component of reward learning and addiction, via 

a D1 dopamine receptor‐mediated mechanism (Ehlinger 

et al. 2016). This persistent form of nicotine‐induced neu‐

roplasticity has the potential to alter synaptic connectivity 

within reward‐processing centers and enhance the addic‐

tive effects of drugs of abuse.

Attention and Cognition. Both cognitive improve‐

ments (Jasinska et  al. 2014) and cognitive deficits (Hall 

et  al. 2014) have been reported after nicotine exposure 

in healthy human adults, while smoking during adoles‐

cence impairs cognition and attention processes. Results 

of a genetically sensitive, longitudinal “concordant” 

and “discordant” twin study from the Netherlands Twin 

Registry indicated a larger increase in attention prob‐

lems from adolescence to adulthood in twins who smoked 

than in their never‐smoking co‐twins (Treur et al. 2015). 

In another study, adolescent smokers were found to have 

chronic impairments in the accuracy of their working 

memory (e.g., in processing information from two sensory 

modalities simultaneously), which were more severe with 

an earlier age of onset of smoking (Jacobsen et al. 2005). 

Functional imaging studies have shown that 24‐hour 

smoking abstinence in adolescent smokers causes acute 

impairments of verbal memory and working memory, 

along with chronic decrements in cognitive performance 

(Jacobsen et al. 2007a). In another study, adolescent users 

of conventional cigarettes showed decreased prefrontal 

cortex activation (versus never smokers) during attention 

tasks, and duration of smoking (in years) was directly cor‐

related with the extent of reduction in prefrontal cortical 

activity (Musso et al. 2007).

Thus, longitudinal and imaging studies in humans 

provide support for the hypothesis that adolescent use of con‐

ventional cigarettes has both acute and long‐term effects on 

attention and memory. Although nicotine exposure cannot 

be cited as the sole cause of cognitive defects (or even one 

of several combined effects in humans), other studies have 

shown that adolescent nicotine exposure in rats induces 

lasting synaptic changes in the prefrontal cortical regions 

critical for normal attention, memory, and cognition that 

likely underlie observed impairments in attentional and 

cognitive function (Bergstrom et  al. 2008). Adolescent 

nicotine exposure in rats has induced impairments in 
Health Effects of E-Cigarette Use Among U.S. Youth and Young Adults 107

E-Cigarette Use Among Youth and Young Adults

stimulus‐response‐discrimination‐learning processes but 

not in abstract rule‐learning processes, which are dependent 

on dissociable cognitive systems, thus showing the selective 

effects of nicotine (Pickens et al. 2013). In addition, adoles‐

cent, but not postadolescent, treatment of rats with nico‐

tine resulted in diminished attention span and enhanced 

impulsivity in adulthood (Counotte et al. 2009, 2011). The 

biological causes of these cognitive disturbances (reduced 

attention span and impulse control) were associated with 

reduced regulation of prefrontal cortex excitatory synapses 

function in metabotropic glutamate receptor 2 (mGluR2) 

(Counotte et al. 2011; Goriounova and Mansvelder 2012). 

In addition, hippocampal function, which is critical for 

memory, was altered in adult mice by nicotine exposure 

during adolescence. Contextual fear conditioning—a 

hippocampus‐dependent task in which animals learn and 

remember to associate a fearful stimulus (e.g., a foot shock) 

with a particular context—was disrupted in adult mice that 

had been treated during adolescence with chronic nicotine 

but not following chronic treatment with nicotine in adult‐

hood (Portugal et al. 2012). Rodent studies have implica‐

tions for human adolescents, suggesting that exposure to 

tobacco during youth may lead to long‐lasting changes in 

behavioral and neuronal plasticity into adulthood.

Mood Disorders. Adolescents with symptoms of 

mental health disorders (e.g., anxiety, aggressive and dis‐

ruptive behaviors, mood disorders) are at increased risk 

for initiation of conventional cigarette use and long‐

term nicotine dependence compared with those without 

such disorders (Gehricke et al. 2007; Morris et al. 2011). 

Although this risk may reflect a common genetic predis‐

position, or the use of nicotine to self‐medicate in the 

hope of improving mental health symptoms, the question 

arises of whether the smoking of conventional cigarettes 

by adolescents contributes to the development of mood 

disorders. A meta‐analysis of existing studies showed con‐

sistent evidence that both tobacco use and dependence 

on tobacco products among adolescents indeed increased 

their risk of anxiety disorders (Moylan et al. 2012). Other 

studies have shown that an early onset of smoking is asso‐

ciated with a shorter time to first onset of an anxiety dis‐

order (Jamal et al. 2011), and there is a positive association 

between adolescent smoking, particularly through a nico‐

tine pathway, and anxiety in early adulthood (Moylan et al. 

2013). Bidirectional relationships between adolescent 

smoking and disruptive disorders (e.g., ADHD; opposi‐

tional defiant disorder [ODD] [Griesler et al. 2011]) as well 

as depression (Tjora et al. 2014) also have been reported, 

while a longitudinal birth cohort found evidence to sup‐

port a causal relationship between teen smoking and onset 

of depression (Boden et al. 2010). Although these findings 

are complex and warrant further study using comparisons 

of genetic polymorphisms associated with smoking or 

twin and sibling discordant/concordant studies (Munafo 

and Araya 2010; Leventhal and Zvolensky 2015), they do 

suggest that nicotine exposure during adolescence could 

contribute to long‐term mental health disorders.

Findings of animal studies support the theory that 

adolescent nicotine exposure results in long‐term alter‐

ations in emotional response, specifically enhanced anx‐

iety and fear (Slawecki et al. 2003; Smith et al. 2006), and 

in persistent alterations in serotonin systems involved in 

mediating mood disorders by reprogramming the future 

response of 5‐HT systems to nicotine (Slotkin and Seidler 

2009). Even a single day of nicotine treatment in adoles‐

cent rats can enhance sensitivity to aversive stimuli later 

in life and result in a depression‐like state in adulthood 

that is normalized by treatment with nicotine or antide‐

pressants (Iniguez et al. 2009).

In summary, given the existing evidence from 

human and animal studies of the detrimental impact of 

nicotine exposure on adolescent brain development, the 

use of e‐cigarettes by youth should be avoided and actively 

discouraged. Both preadolescence and adolescence are 

developmental periods associated with increased vulner‐

ability to nicotine addiction, and exposure to nicotine 

during these periods may lead to long‐lasting changes in 

behavioral and neuronal plasticity. Studies reveal that for 

most tobacco users, initial use begins before 18 years of 

age. Moreover, in some adolescents, symptoms of nico‐

tine dependence can develop after exposure to very low 

levels of nicotine—less than 100 cigarettes. Cross‐species 

studies have identified characteristics of the adolescent 

brain that may render it vulnerable at this age to nicotine 

uptake in the form of equivalent doses via nonsmoking 

administration mechanisms. In addition, animal models 

of nicotine exposure in adolescence reveal neural and 

behavioral alterations consistent with an increased like‐

lihood of future nicotine use, increased activation of 

reward pathways and, unlike in adult animals, decreased 

aversive effects. Regarding e‐cigarettes, data demonstrate 

adolescent use of these devices is associated with use of 

tobacco, alcohol, and other drugs (Dutra and Glantz 2014; 

Kristjansson et al. 2015; Wills et al. 2015a, b; Schneider 

and Diehl 2016). Finally, animal and human studies sug‐

gest a bidirectional relationship between the smoking of 

conventional cigarettes and exposure to nicotine during 

adolescence and factors related to disruptive disorders, 

such as ADHD and ODD that impair academic perfor‐

mance, as well as to depression. Because the adolescent 

brain is still developing, nicotine use during adolescence 

can disrupt the formation of brain circuits that con‐

trol attention, learning, and susceptibility to addiction. 

Further research is warranted to more fully understand 

the effects of e‐cigarette use on youth.
A Report of the Surgeon General

108 Chapter 3

Nicotine Exposure from Maternal Nicotine 

Consumption: Prenatal and Postnatal Health 

Outcomes

Prenatal nicotine exposure through maternal ciga‐

rette use during pregnancy is one of the most widespread 

perinatal insults in the world (Levin and Slotkin 1998; Xiao 

et al. 2008; USDHHS 2014). Despite medical and societal 

sanctions and ongoing public health campaigns, the prev‐

alence of maternal cigarette use during pregnancy in the 

United States was estimated to be 11–15% in 2013 (Tong 

et al. 2013). Smoking rates were even higher among women 

who were poor, young, or less educated, with rates as high 

as 25–30%, indicating that infants born to mothers who are 

poor have disproportionately higher exposure to nicotine 

(Dietz et al. 2011; Hamilton et al. 2012; Tong et al. 2013). 

Despite these adverse consequences, an estimated one‐half 

of pregnant smokers continue to smoke into the third tri‐

mester (Osterman et al. 2013; Tong et al. 2013).

Because adults who use e‐cigarettes can achieve 

plasma nicotine concentrations similar to those found 

among smokers of equivalent amounts of conventional 

cigarettes (Vansickel et  al. 2010; Lopez et  al. 2016; 

St. Helen et al. 2016), it is important that research con‐

tinues in this area. Nicotine has been shown to cross the 

placenta and has been found in placental tissue as early 

as 7 weeks of embryonic gestation, and nicotine concen‐

trations are higher in fetal fluids than in maternal fluids 

(Luck et  al. 1985; Jauniaux et  al. 1999). nAChRs are 

widely distributed in the fetal brain. As has been clearly 

demonstrated in animal models, acetylcholine acts on 

nAChRs to modulate functional connections during crit‐

ical periods of development when regions are most sen‐

sitive to environmental input (Dwyer et al. 2008). When 

nicotine in the maternal bloodstream crosses the pla‐

cental barrier, it binds to these receptors (Pentel et  al. 

2006; Wong et  al. 2015), and in rodents this can result 

in long‐term changes in neural structure and function. 

Results from animal studies show consistent associations 

between prenatal nicotine exposure and upregulation of 

nAChRs associated with disruption of fetal brain cell rep‐

lication and differentiation (Slotkin 1998). Highlighting 

the role of nicotine in the effects of maternal smoking 

during pregnancy, nAChRs have been shown to be present 

in the human embryonic brain from 5 weeks of gesta‐

tion (Hellstrom‐Lindahl et  al. 1998), and their normal 

maturation is altered in a region‐ and receptor subtype‐

dependent fashion by maternal cigarette smoking during 

pregnancy (Falk et al. 2005; Duncan et al. 2008). In those 

brainstem nuclei important for arousal, prenatal nicotine 

exposure decreases [3H]‐nicotine binding (Duncan et al. 

2008) and prevents normal age‐related increases in α4 

and α7 mRNA (Falk et al. 2005).

Prenatal nicotine exposure also has been associated 

with dysregulation of catecholaminergic, serotonergic, 

and other neurotransmitter systems. In addition, animal 

work suggests significant adverse effects of nicotine alone 

at levels commensurate with exposure to secondhand 

smoke (10‐fold below those seen in active smokers), and 

that the non‐nicotine components of tobacco smoke can 

exacerbate nicotine’s teratogenic effects (Slotkin et  al. 

2015). Offermann (2015) concluded that e‐cigarettes 

emit many harmful chemicals into the air and that indi‐

rect exposure to nicotine exceeded exposure‐level stan‐

dards for noncarcinogenic health effects established by 

the California Environmental Protection Agency. No safe 

level of prenatal nicotine exposure has been established 

(England et al. 2015).

Airborne nicotine exposure through secondhand 

aerosol from e‐cigarettes has been observed, as has sali‐

vary cotinine concentrations of nonsmokers in the homes 

of e‐cigarette users (Ballbe et al. 2014; Czogala et al. 

2014). Ballbe and colleagues (2014) reported the geo‐

metric means of airborne nicotine were 0.74 μg/m3 in the 

homes of smokers, 0.13 μg/m3 in the homes of e‐cigarette 

users, and 0.02 μg/m3 in the homes of nonsmoking con‐

trols. While airborne nicotine exposure from combustible 

cigarette smoke was 5.7 (Ballbe et al. 2014) to 10 times 

higher (Czogala et al. 2014) than e‐cigarette aerosol, one 

study reported only a twofold increase in salivary cotinine 

(0.38 ng/ml in the homes of smokers versus 0.19 ng/ml in 

the homes of e‐cigarette users) (Ballbe et al. 2014), and 

another study found that exposure to cigarette smoke and 

exposure to e‐cigarette aerosol had similar effects on the 

serum cotinine levels of bystanders (Flouris et al. 2013). 

Thus, the passive exposure to nicotine from e‐cigarette 

smoking has been reported to be just as large (Flouris 

et al. 2013; Grana et al. 2013) or lower than (Czogala et al. 

2014) conventional cigarettes, but exposure to nicotine 

from e‐cigarette smoking is not negligible and is higher 

than in nonsmoking environments. This evidence sug‐

gests the importance of avoiding secondhand exposure 

of e‐cigarette vapor and secondhand smoke during preg‐

nancy (Flouris et al. 2013; Grana et al. 2013; Czogala et al. 

2014).

Of the components of tobacco smoke, nicotine 

has been cited as the most important toxicant in terms 

of interfering with fetal development. Because of the 

health risks to the developing fetus associated with nico‐

tine exposure during pregnancy, the U.S. Food and Drug 

Administration (FDA) (2015) recommends that pregnant 

women seek medical approval before using NRT, and the 

American College of Obstetricians and Gynecologists

(2011) recommends consideration of NRT only if a woman 

fails behavioral interventions to quit smoking conven‐

tional cigarettes and has discussed the potential harms 
Health Effects of E-Cigarette Use Among U.S. Youth and Young Adults 109

E-Cigarette Use Among Youth and Young Adults

and benefits of NRT with her physician. NRT is most often 

used during pregnancy as a last resort to avoid exposing 

the fetus to the other toxic ingredients found in con‐

ventional tobacco smoke (Fiore et al. 2008). A Cochrane 

Database systematic review concluded that both the effec‐

tiveness and safety of NRT during pregnancy are unclear 

(Coleman et al. 2012). Table A3.1‐4 in Appendix 3.1 pres‐

ents a summary of studies in humans on the effects of 

tobacco exposure on fetal brain development.

Even with a firm understanding of the negative 

health consequences of nicotine on the developing fetus 

(Fiore et  al. 2008; USDHHS 2014; Ekblad et  al. 2015), 

little is known about the prevalence of e‐cigarette use 

among pregnant women or the direct harmful effects 

on their fetus by other toxicants delivered by the aerosol 

from e‐cigarettes (England et al. 2015; Suter et al. 2015). 

In one of the few studies identified, a survey of 316 preg‐

nant women in a Maryland clinic found that the majority 

had heard of e‐cigarettes, 13% had ever used them, and 

0.6% were current daily users (Mark et al. 2015). These 

findings are of concern because the dose of nicotine 

delivered by e‐cigarettes can be as high or higher than 

that delivered by conventional cigarettes. Therefore, 

plasma nicotine concentrations delivered while using 

e‐cigarettes have the potential to harm the developing 

fetus. Furthermore, in 2013 in the United States, there 

were 26.5 births for every 1,000 adolescent females 

(15–19 years of age), or 273,105 babies born to females 

in this age group (Hamilton et al. 2013). Currently, the 

rate of e‐cigarette use among pregnant adolescents is 

unknown, but the effects of nicotine and the potential for 

harm by other e‐cigarette toxicants indicate that the use 

of e‐cigarettes is a fetal risk factor among pregnant ado‐

lescent girls.

As outlined below, the specific effects of nicotine 

on prenatal development and postnatal outcomes include 

sudden infant death syndrome (SIDS) and may include 

altered development of the corpus callosum, deficits in 

auditory processing, and alterations in appetitive behavior, 

attention, and cognition.

SIDS. SIDS is the sudden and unexplained death of 

an infant younger than 1 year of age (Krous 2014). Maternal 

smoking and infant exposure to secondhand smoke have 

been causally associated with SIDS, with 20–29% of deaths 

from SIDS attributable to maternal smoking of conven‐

tional cigarettes during pregnancy (Dietz et  al. 2010; 

Zhang and Wang 2013; USDHHS 2014). Prenatal exposure 

to cigarettes and to smokeless tobacco have been associ‐

ated with increased risk for apnea events, which have been 

linked to increased risk for SIDS (Gunnerbeck et al. 2011; 

Zhang and Wang 2013; Inamdar et al. 2015).

Although the mechanistic pathways underlying 

SIDS remain largely unknown, nicotine has effects on 

pathways that could be related to SIDS and is related 

to known risk factors, particularly lung and respira‐

tory development (England et al. 2015; Holbrook 2016; 

Spindel and McEvoy 2016). Evidence from animal models 

supports the hypothesis that prenatal nicotine exposure 

alters both fetal autonomic function and arousal, which 

could increase the risk of SIDS (Slotkin 1998; Task Force 

on Sudden Infant Death Syndrome and Moon 2011). In 

humans, a dose–response relationship between cotinine 

(the major nicotine metabolite) and altered arousal pat‐

terns has been shown in preterm infants (Richardson 

et  al. 2009), and this relationship is suggestive of nico‐

tine’s role in arousal deficits that could be linked to SIDS. 

There is widespread distribution of nAChRs in the brain‐

stem nuclei in both humans and animals that control car‐

diopulmonary integration and arousal in the newborn 

(Dwyer et  al. 2008). In some animal studies, prenatal 

exposure to nicotine has increased mortality in newborns 

that were exposed to reduced oxygen (Slotkin et al. 1995; 

Fewell and Smith 1998). Prenatal exposure to nicotine 

is also associated with altered serotonin signaling in the 

brainstem in the rat model, leading to an exaggerated tri‐

geminocardiac reflex and resulting in bradycardia, hypo‐

tension, and apnea (Gorini et al. 2013).

Altered Development of the Corpus Callosum. The 

corpus callosum, the largest white matter structure in 

the brain, facilitates communication between the left and 

right cerebral hemispheres. Several human studies have 

revealed alterations in the structure of the corpus callosum 

in offspring following their exposure to maternal cigarette 

use during pregnancy (Jacobsen et al. 2007b; Paus et al. 

2008). In animal models, prenatal exposure to nicotine 

has been shown to result in widespread alterations in gene 

expression in the brains of adolescent offspring (Cao et al. 

2011, 2013; Wei et al. 2011). In particular, the expression 

of a number of genes involved in myelination—the forma‐

tion of white matter via the addition of protective myelin 

sheaths to axons—is altered in a sex‐dependent manner, 

with upregulation in males and downregulation in females 

(Cao et al. 2013). Such changes in the expression profiles 

of myelin‐related genes may influence the structure and 

function of white matter, and both hypermyelination and 

hypomyelination have been associated with cognitive defi‐

cits (Quaranta et al. 2002; Sokolov 2007).

Deficits in Auditory Processing. A number of 

human studies, using a variety of methods, have inves‐

tigated the effects of maternal cigarette smoking during 

pregnancy on auditory processing from the fetal period 

through childhood (Jacobson and Morehouse 1984; 

Kristjansson et  al. 1989; McCartney et  al. 1994; Franco 

et al. 1999; Leech et al. 1999; Cowperthwaite et al. 2007). 

Deficits in auditory processing in fetuses are of concern 

because they affect later language development (Kisilevsky 
A Report of the Surgeon General

110 Chapter 3

and Davies 2007; Kisilevsky et al. 2014). Various studies in 

infants have investigated the brain’s physiological activity 

response to auditory stimuli (the cochlea translates sound 

into nerve impulses to be sent to the brain), neuroelectric 

activity of the auditory nerve, and cochlear response (Key 

et al. 2007; Korres et al. 2007; Kable et al. 2009; Peck et al. 

2010; Katbamna et al. 2013). Key and colleagues (2007) 

reported prenatal exposure to cigarette use (compared 

with nonexposed infants) to be associated with alterations 

in hemispheric asymmetry and suboptimal brain activity 

related to speech processing in otherwise healthy new‐

borns at least 2 days of age. Korres and associates (2007) 

found altered cochlear responses to auditory stimuli 

in newborns that were exposed to maternal cigarette 

smoking (n = 200) compared with those that were unex‐

posed (n = 200), regardless of degree of cigarette exposure. 

Similar findings were reported by Durante and colleagues 

(2011) in two case‐control studies.

Two additional studies investigated effects of 

maternal cigarette use during pregnancy on auditory 

brainstem responses in newborns (≤2 days old) (Peck et al. 

2010) and infants (6 months old) (Kable et al. 2009). Both 

studies found greater neuroelectric response to sound 

stimuli, a phenomenon that may disrupt an infant’s ability 

to encode auditory information, potentially leading to def‐

icits in language development. Furthermore, both studies 

demonstrated dose–response relationships between 

altered auditory processing and maternal cotinine levels. 

Finally, in a study of a small sample of newborns that 

sought to understand the direct biological pathway, 

maternal smoking during pregnancy produced changes in 

newborn cochlear and auditory brainstem functions and 

changes in placental gene expression in genes that appear 

to modulate the motility of cochlear hair cells (Katbamna 

et al. 2013). Thus, all three studies indicate effects based 

on consumption of conventional cigarettes, and they high‐

light the possibility of a mediating role of maternal nico‐

tine use in altered infant auditory processing, although 

further work must rule out confounding effects and effect 

modification by other constituents (e.g., arsenic, benzene, 

and cadmium).

A study using functional magnetic resonance 

imaging (fMRI) in older offspring exposed to tobacco 

in utero assessed response to auditory and visual atten‐

tion tasks in adolescent smokers (Jacobsen et al. 2007a). 

Teens whose mothers smoked during pregnancy exhibited 

decreased accuracy in the tasks, with greater activation 

of both the temporal lobe and the occipital lobe, regions 

of the brain that are critical for auditory and visual pro‐

cessing. Additive effects of maternal cigarette use during 

pregnancy and of adolescent smoking on activation of the 

temporal and occipital lobes also emerged, indicative of 

reduced coordination among brain regions during audi‐

tory attention tasks.

Animal studies have shown that nAChRs play a 

critical developmental role in establishing synaptic con‐

nections between sensory thalamic afferents and those 

cortical targets that are necessary for normal sensory 

processing (Table A3.1‐5 in Appendix 3.1). Brief nicotine 

exposure during this critical postnatal period of sensory 

cortex development disrupts glutamate transmission 

(Aramakis et al. 2000) and eliminates nAChR regulation of 

signal processing in the adult auditory cortex, inhibiting 

normal auditory learning (Liang et  al. 2006). Animals 

that are prenatally exposed to nicotine also exhibit defi‐

cits in cognitive processing in response to an auditory cue, 

which appears to be mediated by a loss of function of the 

nAChR β2 subunit (Liang et al. 2006; Horst et al. 2012).

Appetitive and Consummatory Behaviors. Clinical 

studies and animal studies have linked prenatal exposure 

to nicotine to subsequent appetitive behaviors (an active 

searching process that is performed consciously) and con‐

summatory behaviors (such as ingestion of food or drugs) 

in offspring. Associations have been demonstrated in 

humans between maternal cigarette use during pregnancy 

and risk to the child of smoking uptake/nicotine depen‐

dence, drug abuse, and obesity; parallel relationships have 

been shown in animal models between prenatal exposure 

to nicotine and similar appetitive behaviors of offspring.

Parental use of tobacco is one of many well‐known 

risk factors for offspring initiation of tobacco, progres‐

sion to heavy use, and nicotine dependence. Tobacco use 

by parents influences their children through social, envi‐

ronmental, cognitive, and genetic mechanisms (USDHHS 

2012). As a subset of these influences, mothers’ use of 

tobacco during pregnancy has been studied as an inde‐

pendent risk factor and has been associated with offspring 

susceptibility, initiation, regular use, and dependence 

(Kandel et al. 1994; Griesler et al. 1998; Kandel and Udry 

1999; Buka et  al. 2003; Lieb et  al. 2003; Oncken et  al. 

2004; Al Mamun et  al. 2006; O’Callaghan et  al. 2009; 

Tehranifar et  al. 2009; Agrawal et  al. 2010; Rydell et  al. 

2012; Weden and Miles 2012; Stroud et al. 2014; Shenassa 

et al. 2015). Wakschlag and colleagues (2010, 2011) sug‐

gest that maternal smoking during pregnancy has a ter‐

atologic effect with abnormalities stemming from the in 

utero environment which disrupt neural (Kandel et  al. 

1994; Jacobsen et  al. 2006) and dopamine systems that 

promote sensitivity to nicotine dependence (Kandel et al. 

1994; Selya et al. 2013). For example, nicotinic receptors 

of laboratory animals exposed to nicotine in utero are 

upregulated, suggesting a latent vulnerability to nicotine 

dependence among animals exposed to nicotine in utero 

(Slotkin et al. 2006, 2015).
Health Effects of E-Cigarette Use Among U.S. Youth and Young Adults 111

E-Cigarette Use Among Youth and Young Adults

At issue with all human studies investigating 

maternal use of tobacco during pregnancy and offspring 

use of tobacco is isolating the independent effect on the 

fetus in relation to the other social, environmental, and 

cognitive factors that also predict offspring tobacco use. 

After controlling for maternal smoking during the off‐

spring’s childhood, several studies have reported that 

maternal smoking during pregnancy is associated with 

higher nicotine dependence in offspring (Kardia et  al. 

2003; Lieb et al. 2003; Selya et al. 2013; Shenassa et al. 

2015), increased or earlier smoking initiation, and heavier 

smoking among adolescent girls and adult offspring 

(Kandel et al. 1994; Cornelius et al. 2005). However, the 

association was attenuated and nonsignificant among sev‐

eral studies that controlled for a variety of environmental, 

social, and cognitive confounders between maternal cig‐

arette use during pregnancy and initiation of offspring 

smoking (but not nicotine dependence) (Cornelius et al. 

2005; Roberts et al. 2005; Munafo et al. 2006; Kandel et al. 

2007; D’Onofrio et al. 2012; Rydell et al. 2014; Taylor et al. 

2014), leaving speculation for the independent effect. In 

summary, evidence from animal models offers a biologic 

mechanism for, and human evidence is suggestive of, an 

association between maternal tobacco use during preg‐

nancy with offspring smoking and nicotine dependence, 

but is insufficient to infer causation. Further research and 

longitudinal studies that examine these outcomes while 

assessing the full spectrum of environmental, social, and 

cognitive mediating pathways are needed to disentangle 

these issues.

A smaller set of literature has documented associa‐

tions between maternal cigarette smoking during preg‐

nancy and use of other substances by the child (Fergusson 

et al. 1998; Weissman et al. 1999; Porath and Fried 2005; 

Nomura et al. 2011). In utero exposure to nicotine also 

affects behavioral responses for drug rewards in both ado‐

lescent and adult experimental animals. Prenatal expo‐

sure to nicotine increases the preference of adolescents 

for a saccharin solution containing nicotine compared 

with saccharin alone (Klein et al. 2003), and it results in 

self‐administration of nicotine either during acquisition 

of the task (Chistyakov et al. 2010) or after forced absti‐

nence (Levin et al. 2006). Prenatal exposure to nicotine 

also increases subsequent oral intake of alcohol (Chang 

et al. 2013), and intravenous self‐administration of both 

cocaine and methamphetamine is enhanced in a dose‐

dependent manner in adolescent rats (Franke et al. 2008) 

and adult rats (Lacy et al. 2014).

 In contrast, in a study that used a discordant sib‐

ling pair design to reduce confounding by genetic and 

environmental factors, initial associations between pre‐

natal smoking and alcohol use disorder were attenuated 

and were no longer statistically significant (D’Onofrio 

et  al. 2012). In a large longitudinal study that spanned 

40 years, Shenassa and colleagues (2015) found evidence 

to support effects on nicotine dependence among chil‐

dren of mothers who smoked during pregnancy, but no 

effects on their progression to marijuana dependence 

were observed. A possible explanation for these discordant 

findings is suggested by a study that found significant 

effects from prenatal smoking of conventional cigarettes 

on drug use among adolescents, but showed that these 

effects were restricted to a genetic subpopulation of car‐

riers of a specific α6 nAChR gene (rs2304297) polymor‐

phism (Lotfipour et al. 2010). In sum, a number of studies 

have documented associations between cigarette use by 

the mother during pregnancy and smoking initiation, 

heavy use, and nicotine dependence among her children, 

although control of confounding reduces this associa‐

tion. In addition, the literature is sparse and inconsistent 

regarding a connection between maternal cigarette use 

during pregnancy and the use of nontobacco substances 

by the child.

A large body of literature has demonstrated effects 

of maternal cigarette use during pregnancy on weight 

levels and obesity in childhood. For example, three meta‐

analytic reviews found a 47–64% increased risk of obe‐

sity in children following exposure to maternal cigarette 

smoking during pregnancy (Oken et al. 2008; Ino 2010; 

Weng et  al. 2012; Behl et  al. 2013). Additional system‐

atic reviews (Bruin et al. 2010) and other studies (Harrod 

et al. 2015; La Merrill et al. 2015; Mourtakos et al. 2015; 

Bao et  al. 2016) have all concluded that prenatal expo‐

sure to nicotine likely acts as a developmental obesogen 

in humans. However, unmeasured residual confounding 

or confounding by familial factors, which have not been 

fully explored, could attenuate the observed associations 

(Gilman et al. 2008; Iliadou et al. 2010). Animal studies 

support the epidemiologic literature suggesting a poten‐

tially causal relationship here by defining biologic path‐

ways (Wong et al. 2015). Fetal and neonatal exposure to 

nicotine in rodents has resulted in neurochemical, neu‐

robehavioral, and metabolic changes in the children that 

are consistent with obesity and type 2 diabetes (Williams 

and Kanagasabai 1984; Newman et al. 1999; Grove et al. 

2001; Chen and Kelly 2005; Gao et  al. 2005; Holloway 

et al. 2005).

In humans, studies involving structural MRI and 

fMRI have shown alterations in the size and sensitivity of 

brain reward centers in the teenage offspring of maternal 

smokers. Several of these studies revealed a thinning of 

the orbitofrontal cortex among persons who were prena‐

tally exposed to maternal cigarette smoking, a thinning 

that was associated with drug use and experimentation 

during adolescence (Toro et  al. 2008; Lotfipour et  al. 

2009); decreased amygdalar volume, which is associated 
A Report of the Surgeon General

112 Chapter 3

with increased fat intake (Haghighi et  al. 2013); and 

altered response to reward anticipation in the ventral stri‐

atum, an area associated with risk taking and drug use 

(Muller et al. 2013). In addition, highlighting the role of 

altered nicotinic pathways in the disruption of neural cir‐

cuits from prenatal tobacco exposure, changes in striatal 

volume, and a propensity for drug use in adolescent off‐

spring have been linked to interactions between prenatal 

exposure to cigarette smoking and a polymorphism in 

the gene encoding the α6 nAChR (Lotfipour et al. 2010). 

Structural alterations in the orbital frontal cortex have 

also been shown to result from interactions between 

maternal cigarette smoking during pregnancy and poly‐

morphisms of brain‐derived neurotrophic factor, a growth 

factor that regulates growth and differentiation of new 

neurons and supports existing neurons (Lotfipour et  al. 

2009). Although these clinical findings are specific to con‐

ventional cigarettes, they converge with results of animal 

studies of the effects of prenatal nicotine on brain reward 

centers and thus highlight the potential pernicious effects 

of e‐cigarettes in pregnant women.

Animal studies have shown that the dopamine 

system, which is critically involved in satisfaction‐seeking 

or appetitive behaviors, is modulated by nAChRs from the 

fetal period to adulthood (Azam et al. 2007). Prenatal nico‐

tine exposure alters dopamine’s content, turnover, release, 

and receptor expression in forebrain regions, which are 

important for motor and cognitive functions (Navarro 

et al. 1988; Richardson and Tizabi 1994; Muneoka et al. 

1999; Zhu et al. 2012) and for assigning motivational value 

to natural and drug rewards (Kohlmeier 2015; McNair and 

Kohlmeier 2015). Prenatal exposure to nicotine also mod‐

ifies the structure of dendritic targets of dopamine inner‐

vations in the nucleus accumbens (a critical component 

of reward learning and addiction) (Mychasiuk et al. 2013) 

and alters neuronal signaling that affects dopamine func‐

tion (Chang et al. 2013; Morgan et al. 2013).

Prenatal exposure to nicotine has been shown in 

a variety of animal studies to induce complex effects on 

behavioral response to natural rewards. Although adoles‐

cent offspring of nicotine‐exposed mothers show an ini‐

tial decrease in motivation to work for sucrose reward 

(Franke et al. 2008), they exhibit enhanced sensitivity to 

the rewarding effects as the task becomes harder (Lacy 

et  al. 2012). Prenatal exposure to nicotine also results 

in enhanced intake of fatty foods, with no change in the 

intake of normal chow (Chang et al. 2013).

Attention and Cognition. Numerous human 

studies have investigated the effects of maternal cigarette 

use during pregnancy on disruptive behavior and atten‐

tion deficits in the child. The 2014 Surgeon General’s 

report included results of a systematic review of effects 

of maternal cigarette use during pregnancy on disrup‐

tive‐behavior disorders—including ADHD, conduct dis‐

order, and ODD—in offspring (USDHHS 2014). The 

evidence for effects of maternal cigarette use during 

pregnancy on disruptive‐behavior disorders, and ADHD 

in particular, was suggestive but not sufficient to infer 

a causal relationship. Several systematic reviews using 

meta‐analyses have found evidence for associations 

between exposure to maternal cigarette use during preg‐

nancy and ADHD in offspring, including dose–response 

relationships between number of cigarettes smoked per 

day and ADHD symptoms (Linnet et  al. 2003; Langley 

et  al. 2005; Latimer et  al. 2012; Massey et  al. 2016). 

However, similar to effects on nicotine dependence and 

obesity in offspring, the possibility of unmeasured con‐

founding remains (D’Onofrio et  al. 2008; Thapar et  al. 

2009; Langley et  al. 2012). Evidence for associations 

with maternal cigarette use during pregnancy is perhaps 

more consistent for offspring conduct disorders than it 

is for ADHD. In particular, although some studies that 

used a gene–environment interaction design or a pro‐

pensity score‐matching approach to exposure to control 

for confounding, they found no effect of maternal cig‐

arette smoking during pregnancy on conduct disorders

(D’Onofrio et al. 2008; Gilman et al. 2008; Boutwell and 

Beaver 2010; Lavigne et al. 2011). However, several other 

studies—including a meta‐analytic review across three 

studies using “genetically sensitive”2

2Genetically sensitive designs typically include monozygotic and dizygotic twins and a broader inclusion of sibling pairs, mother–child 

pairs, and grandparent–grandchild pairs. Genetically sensitive multigroup designs allow for simultaneous testing of additive and nonadditive genetic, common, and specific environmental effects, including cultural transmission and twin-specific environmental influences.

research designs—

have suggested a direct causal relationship between 

maternal smoking during pregnancy and conduct disor‐

ders in offspring (McCrory and Layte 2012; Gaysina et al. 

2013; Kuja‐Halkola et  al. 2014; Estabrook et  al. 2015; 

Paus and Pausova 2015).

To explore the potential role of nicotine exposure in 

these associations, a small number of studies have included 

a prospective measure of confirmed tobacco exposure, 

maternal cotinine levels, in addition to maternal report 

of smoking, to study relationships with disruptive behav‐

iors among offspring (Wakschlag et al. 2011; O’Brien et al. 

2013; Massey et al. 2016). Wakschlag and colleagues (2011) 

found associations between maternal cigarette smoking 

and aggression and noncompliance among offspring. 

Studies have also shown alterations in the structure and 
Health Effects of E-Cigarette Use Among U.S. Youth and Young Adults 113

E-Cigarette Use Among Youth and Young Adults

function of the orbital frontal cortex, a  region impor‐

tant for emotional regulation and cognition, in relation 

to maternal cigarette smoking during pregnancy (Toro 

et al. 2008; Bennett et al. 2009). Consistent with animal 

models of altered dopamine regulation, two studies have 

shown interactions of maternal cigarette smoking during 

pregnancy with dopamine regulation genotype (DAT1) in 

influencing disruptive‐behavior phenotypes in offspring 

(Wakschlag et  al. 2011; O’Brien et  al. 2013). In another 

study, Wakschlag and colleagues (2010) demonstrated a 

sex‐dependent interaction of maternal smoking during 

pregnancy with monoamine oxidase A (MAOA) geno‐

type, which is associated with the development of anti‐

social behavior. In this study, maternal smoking during 

pregnancy further increased the risk for conduct disorder. 

In sum, although issues of confounding remain, much 

evidence from human studies is suggestive of a causal 

association between maternal cigarette smoking during 

pregnancy and disruptive behaviors among offspring. 

This was confirmed by the 2014 Surgeon General’s report 

on tobacco (USDHHS 2014). Since then, newer studies, 

controlling for personal and genetic confounders, have 

reported significant associations as well as nonsignificant, 

attenuated associations. Biologic evidence of nicotine‐

induced alterations in dopamine regulation also provides 

a possible mechanism for the role of nicotine in these 

outcomes.

Animal studies have shown that cholinergic modu‐

lation of prefrontal cortex function, via nAChRs, is essen‐

tial for attention and cognition (Poorthuis and Mansvelder 

2013; Proulx et  al. 2014). Prenatal exposure to nicotine 

alters the morphology and nAChR functional response of 

prefrontal cortical neurons (Mychasiuk et al. 2013; Bailey 

et al. 2014). When tested as adolescents, animals that were 

exposed prenatally to nicotine show some behaviors char‐

acteristic of ADHD. For example, exposed offspring were 

found in two studies to show less impulse control and/or 

slower learning acquisition on two cognitive tests that tax 

attentional processes (Sorenson et  al. 1991; Schneider 

et al. 2012). In addition, some studies have found hyper‐

activity in exposed offspring (Pauly et al. 2004; Schneider 

et al. 2012; Zhu et al. 2012), which was found in another 

study to be transmitted via maternal lineage from one 

generation to the next and to be ameliorated by methyl‐

phenidate treatment across all generations, showcasing 

the long‐term impact of prenatal nicotine exposure (Zhu 

et al. 2014a). This transgenerational transmission of pre‐

natal nicotine‐induced hyperactivity must reflect long‐

term changes to the epigenome (Leslie 2013). Finally, 

emerging animal studies suggest that prenatal exposure 

to nicotine affects the proliferation and maturation of 

progenitor cells to glutamatergic neurons during neu‐

rodevelopment in the medial prefrontal cortex, resulting 

in behavioral impairments in attentional function and 

behavioral flexibility in adulthood (Aoyama et  al. 2016; 

Poon and Leibowitz 2016; Powell et al. 2016).

Summary

Because of the rising prevalence of e‐cigarette use, 

there is potential for widespread nicotine exposure to 

youth and young adults, resulting in nicotine addiction 

and related harmful consequences associated with expo‐

sure to nicotine. During pregnancy, there is neural sensi‐

tivity to the number and volume of substances, including 

nicotine, transported through the placenta. From pre‐

natal development through adolescence and early adult‐

hood, exposure to nicotine poses a serious threat, because 

these are critical times for brain development and brain 

plasticity. Furthermore, youth and young adults are more 

vulnerable than adults to the long‐term consequences 

of nicotine exposure, including susceptibility to nicotine 

addiction and potentially reduced impulse control, deficits 

in attention and cognition, and mood disorders. An addi‐

tional public health concern is exposure to e‐cigarettes 

among persons who have never used conventional tobacco 

products. If the prevalence of e‐cigarette use continues to 

rise among those who do not use conventional tobacco 

products, the harmful consequences of exposure to nico‐

tine will rise accordingly.

The 2014 Surgeon General’s report (USDHHS 2014) 

states there is sufficient evidence to infer that: (a) nicotine 

activates multiple biological pathways through which 

smoking increases risk for disease; (b) nicotine expo‐

sure during fetal development, a critical window for brain 

development, has lasting adverse consequences for brain 

development; (c) nicotine adversely affects maternal and 

fetal health during pregnancy, contributing to multiple 

adverse outcomes such as preterm delivery and stillbirth; 

and (d) nicotine exposure during adolescence, a critical 

window for brain development, may have lasting adverse 

consequences for brain development and cognition. The 

literature presented in this section attempts to differen‐

tiate the risks to fetal and child health associated with nic‐

otine in tobacco versus nicotine alone or in e‐cigarettes. 

Evidence is sufficient to conclude tobacco use increases 

the risk of SIDS (USDHHS 2014), but further research 

is necessary with regard to nicotine alone or nicotine in 

e‐cigarettes. The review finds evidence that tobacco is 

associated with structural brain changes and alterations 

in cognition, attention, and appetitive behaviors in human 

offspring. Less well known is the role that nicotine plays 

in mediating these associations, although animal models 

provide support for a role for nicotine in these outcomes. 

nAChRs, the chief receptor targets for nicotine, are widely 

expressed in the fetal brain, and their normal functioning 
A Report of the Surgeon General

114 Chapter 3

is negatively affected by smoking and, in animals, by pre‐

natal exposure to nicotine through experimental treat‐

ment. Furthermore, both human genetic studies and 

animal studies implicate a neurotoxic effect of fetal nic‐

otine exposure. Pregnant women and women intending 

to become pregnant should be cautioned against using 

e‐cigarettes to avoid unnecessary nicotine exposure to 

their baby.

Effects of the Inhalation of Aerosol 

Constituents Other than Nicotine

The scientific literature on the health effects of expo‐

sure to constituents other than nicotine in the e‐cigarette 

aerosol is still developing. One study found that after 

5 minutes of ad lib e‐cigarette use, healthy adult cigarette 

smokers showed an increase in airway resistance, but 

no effect on other spirometry parameters such as forced 

vital capacity (FVC), forced expiratory volume in 1 second 

FEV1, and ratios of these values (FEV1/FVC) (Vardavas 

et al. 2012).

A noninvasive marker of airway inflammation is 

the fraction of exhaled nitric oxide (FeNO) (Taylor et al. 

2006; Munakata 2012). NO is a gaseous molecule that pro‐

duces vasodilation and bronchodilation (decreasing resis‐

tance in the respiratory airway and increasing airflow to 

the lungs). FeNO is reduced by acute and chronic ciga‐

rette smoking (resulting in poorer vasodilation and bron‐

chodilation) and is increased among smokers following 

cessation (see Vleeming et al. 2002 for a review). Studies 

examining current adult cigarette smokers revealed a 

reduction in FeNO after use of an e‐cigarette with and 

without nicotine (Vardavas et al. 2012; Marini et al. 2014; 

Ferrari et al. 2015). One study found that these reductions 

did not differ significantly between e‐cigarettes containing 

nicotine and those without nicotine (Marini et al. 2014), 

suggesting non‐nicotine factors mediated the effect.

However, a study of occasional smokers (<10 cig‐

arettes per week), but non‐e‐cigarette users, found an 

increase in FeNO after use of an e‐cigarette containing 

nicotine (Schober et  al. 2014). Furthermore, this study 

found no statistical difference in FeNO after use of an 

e‐cigarette not containing nicotine. This variation in 

findings suggests the impact of e‐cigarette use on FeNO 

may vary based on smoking history, nicotine content of 

e‐liquid, or other environmental or biological factors.

Limited studies have examined chronic exposure 

on the potential inhalation toxicity of PG and VG. Prior 

to e‐cigarettes, consumer products containing these 

chemicals were almost exclusively liquids or creams, or 

the substance was contained in a matrix. Animal models 

have shown few toxicological effects resulting from nose‐

only exposure to VG aerosol, with the exception of min‐

imal or mild squamous metaplasia in rats exposed to the 

highest concentration (0.662 mg glycerol) for 13 weeks 

(Anderson et  al. 1950; Renne et  al. 1992). Other inhala‐

tion studies testing PG in rats and monkeys did not observe 

treatment‐related effects on respiratory physiology, clin‐

ical chemistry, hematology, gross pathology, or respiratory 

tract histology (Robertson et  al. 1947). However, neither 

of these studies examined potential inhalation toxicity of 

PG and VG in humans using e‐cigarette devices. In sum‐

mary, other than nicotine, very little is known from human 

studies about the long‐term health effects of inhaling PG 

and VG from e‐cigarette aerosol, although adverse effects 

have been detected in animal models. Further investigation 

would improve our understanding of the effects of nicotine‐

related compounds, aerosolized solvents (PG and VG), aero‐

solized flavorants, aerosolized adulterants in e‐liquids, and 

toxicants produced during the aerosolization process—or a 

combination of these chemicals.

Aerosolized Nicotine‐Related Compounds

The nicotine used in e‐liquids is extracted from 

tobacco. The extraction process may produce some poten‐

tially harmful tobacco‐specific impurities, including 

minor alkaloids like nornicotine, anatabine, anabasine, 

myosmine, cotinine, nicotine‐N‐oxides (cis and trans iso‐

mers), β‐nicotyrine, and β‐nornicotyrine (Etter et al. 2013; 

Farsalinos et al. 2015a; Lisko et al. 2015; Oh and Shin 2015). 

The correlation between nicotine and the concentrations of 

minor alkaloids is much stronger in conventional tobacco 

products (Jacob et al. 1999) than in e‐cigarettes (Lisko et al. 

2015). While the cause of these differing concentrations of 

minor alkaloids is unknown, Lisko and colleagues (2015) 

speculated potential reasons may derive from the e‐liquid 

extraction process (i.e.,  purification and manufacturing) 

used to obtain nicotine from tobacco, as well as poor quality 

control of e‐liquid products.

The American E‐Liquid Manufacturing Standards 

Association (2014), an industry group with no regula‐

tory authority, has called for the use of U.S. Pharmacopeia 

(USP)‐grade nicotine in its e‐cigarette products. USP 

specifications for nicotine allow for a maximum of 

0.5% (5 mg/g) of a single impurity and 1% (10 mg/g) of 

total impurities (U.S. Pharmacopeia n.d.). Although the 

health implications of nicotine‐related impurities are not 

known, toxicology studies are needed to demonstrate the 

effects of high levels of these products.
Health Effects of E-Cigarette Use Among U.S. Youth and Young Adults 115

E-Cigarette Use Among Youth and Young Adults

Aerosolized Solvents

Although e‐cigarettes produce PG aerosols at levels 

known to cause eye and respiratory irritation to both 

users and nonusers (Offermann 2015), only mild effects 

(e.g., upper respiratory irritation) have been described 

in humans exposed to PG mist for 1 minute (Wieslander 

et al. 2001), and little is known about long‐term effects. 

Inhaling PG can increase the risk of developing asthma 

(Choi et al. 2010). Animal studies of PG and VG aerosol‐

izing agents not produced by e‐cigarettes concluded that 

these substances are relatively safe when inhaled by ani‐

mals for up to 28 days (Werley et al. 2011) or 18 months 

(Robertson et al. 1947).

Particles emitted from e‐cigarettes are assumed 

to be formed from supersaturated PG (i.e., concentra‐

tion beyond the point of saturation) in e‐liquids (Schripp 

et al. 2013). Several studies designed to characterize the 

aerosol generated by e‐cigarettes examined the chemical 

composition of the particles and their concentrations as 

measured by their number and distribution by size (Trehy 

et al. 2011; Ingebrethsen et al. 2012; Schripp et al. 2013; 

Zhang et al. 2013; Fuoco et al. 2014; Ruprecht et al. 2014; 

Saffari et  al. 2014 ; Mikheev et al. 2016). E‐cigarettes 

are recognized as a new source of submicron‐sized par‐

ticles, leading to possible high exposure to these parti‐

cles in users. Concentrations in the range of 109 particles 

× cm‐3 were measured in the mainstream of e‐cigarette 

and colleagues (2013) found that under the conditions 

of a single‐puff experiment, an e‐cigarette generated an 

aerosol having particle sizes in the range of 100–600 nm 

(nanometers), similar to that of conventional cigarettes. 

Mikheev and colleagues (2016) reported that the size dis‐

tribution of e‐cigarette aerosol differs from that of com‐

bustible tobacco smoke and that e‐cigarettes normally 

exhibit a bimodal particle size distribution: nanoparti‐

cles (11–25 nm count median diameter) and submicron 

particles (96–175 nm count median diameter). Each 

mode has comparable number concentrations 

aerosols (Fuoco et al. 2014). An in vitro study by Zhang 

(107–108

particles/cm3). Goel and colleagues (2015) detected radi‐

cals in aerosols from all e‐cigarettes and e‐liquids tested 

(2.5−10.3 x1013 radicals per puff at 3.3 V [voltage]), from 

e‐liquid solvents PG and VG, and from “dry puffing” (over‐

heating of e‐liquid) (Farsalinos et al. 2015c).

Because the aerosols deriving from e‐liquids are 

mainly made of droplets that are expected to dissolve as 

they reach the lung’s epithelium, not only the number but 

also the volume (size) of particles needs to be considered. 

Manigrasso and colleagues (2015) found that e‐cigarettes 

are a source of extremely high doses of particles in the 

human respiratory system. On average, 6.25 ×1010 par‐

ticles were deposited in the respiratory tree after a single 

2‐second puff, an estimated 30% of the daily doses of par‐

ticles for a nonsmoking person. After 10 puffs, the relevant 

mean‐layer thickness of the e‐liquid on the lung epithe‐

lium was comparable to the thickness of surfactant layer 

covering the alveolar and bronchial regions, suggesting 

a higher susceptibility to irritant endpoints (Manigrasso 

et al. 2015). These results demonstrate that e‐cigarettes 

produce submicron‐sized particles and highly oxidizing 

free radicals that may present a potential toxicologic risk 

to e‐cigarette users.

Aerosolized Flavorants

Little is known about the flavorants used in 

e‐cigarettes, and more than 7,700 unique flavors are on 

the market (Zhu et al. 2014b). Flavored e‐cigarette prod‐

ucts are popular with adult users, and sweet and candy‐

like flavors may make these products attractive to children 

and adolescents (Villanti et  al. 2013; Farley et  al. 2014; 

King et al. 2014). Many of the chemicals used in e‐liquid 

flavorings are “generally recognized as safe” for ingesting 

(e.g., in food). However, these substances have not been 

tested adequately for safety when heated at various tem‐

peratures when inhaled in aerosolized form (Barrington‐

Trimis et al. 2014). The Flavor and Extract Manufacturers 

Association of the United States (2015), in an official state‐

ment, notes that ingredients in flavors are evaluated for 

exposure through ingestion only; thus, any results cannot 

be extrapolated to use through inhalation. Further, fla‐

voring compounds often remain undeclared on e‐cigarette 

and e‐liquid packaging (Tierney et al. 2016).

CDC tested 36 e‐cigarette products for 10 flavor 

compounds commonly used as additives in tobacco prod‐

ucts (Lisko et al. 2015). Measurable levels of eucalyptol and 

pulegone were found in the menthol‐flavored varieties for 

all manufacturers. Menthol concentrations ranged from 

3,700 to 12,000 μg/g in flavored e‐liquids, levels similar 

to those found in the filler of conventional cigarettes. 

Interestingly, menthol was found at low concentrations in 

40% of the tobacco‐flavored nonmenthol products tested. 

Other flavor compounds found were camphor, methyl, 

salicylate, pulegone, cinnamaldehyde (CAD), and eugenol 

(Lisko et al. 2015).

Tierney and colleagues (2016) analyzed 30 e‐cigarette 

products on the U.S. market and found 13 products con‐

tained more than 1% flavor chemicals by weight. Among 

the chemicals identified were aldehydes (e.g., benzalde‐

hyde and vanillin), which are categorized as primary irri‐

tants of the respiratory tract (Roberts et al. 2015). Tierney 

and colleagues (2016) also found that tobacco‐flavored 

e‐liquids were derived from confection‐flavored chemicals 

(e.g., bubble gum and cotton candy flavoring) rather than 

tobacco extract.
A Report of the Surgeon General

116 Chapter 3

Some chemicals in e‐cigarettes, although approved 

for ingestion, have established adverse health effects when 

inhaled. In vitro studies of cytotoxicity suggest that dif‐

ferent flavored e‐cigarette products may vary in their 

potential to adversely affect health. Bahl and colleagues 

(2012) reported cytotoxic effects of the solutions used in 

e‐cigarettes that were not attributable to the nicotine but 

to the concentration of chemicals employed as flavors. 

These effects were most pronounced on mouse neural 

stem cells and human embryonic stem cells compared to 

human pulmonary fibroblast (Bahl et al. 2012).

Similar findings were reported by Behar and col‐

leagues (2014) who found a greater cytotoxic effect 

of flavored e‐liquid solutions on human embryonic 

stem cells compared to human pulmonary fibroblast. 

Further, two  cinnamon‐related chemicals, CAD and 

2‐methoxycinnamaldehyde, were particularly cytotoxic at 

doses found in the refill liquids (Behar et al. 2014). CAD, 

which is derived from the essential oil of cinnamon bark, is 

a highly bioactive compound (Jayaprakasha and Rao 2011). 

It has been used as an anticancer agent (Nagle et al. 2012), 

an insecticide (Cheng et al. 2009), and a bactericide (Nostro 

et al. 2012), and it is employed commercially as an additive 

in many foods and fragrances (Cocchiara et al. 2005).

Farsalinos and colleagues (2014a) analyzed 

159 e‐liquids obtained from a variety of manufacturers and 

retailers in Europe and the United States for the presence 

of two flavorings: diacetyl (DA) and acetyl propionyl (AP). 

The study revealed that these substances were present in 

the majority of the samples tested, with a significant pro‐

portion containing both chemicals. Furthermore, Allen and 

colleagues (2016) detected DA above the laboratory limit 

of detection in 39 of 51 flavors tested. DA, also known as 

2, 3‐butanedione, is a member of a general class of organic 

compounds referred to as diketones, α‐diketones, or 

α‐dicarbonyls. It provides a characteristic buttery flavor, 

is naturally found in various foods, and is used as a syn‐

thetic flavoring agent in food products such as butter, car‐

amel, cocoa, coffee, dairy products, and alcoholic beverages. 

Although it is generally recognized as safe when ingested, 

it has been associated with a decline in respiratory func‐

tion in persons exposed to it through inhalation (Egilman 

et al. 2011; Clark and Winter 2015). Inhaling DA and arti‐

ficial butter‐flavored powders and aerosols can cause fixed 

obstructive lung disease in exposed workers (Chaisson et al. 

2010). In addition, it has been implicated in the develop‐

ment of bronchiolitis obliterans, an irreversible respiratory 

disease also called “popcorn lung disease” (Harber et  al. 

2006). AP, also called 2, 3‐pentanedione, is a α‐diketone 

that is chemically and structurally similar to DA. Although 

it has become a popular replacement for DA, acute inhala‐

tion exposure to AP has been shown to cause airway epithe‐

lial damage similar to DA (Hubbs et al. 2012).

The analysis by Farsalinos and colleagues (2014a) 

found that 74.2% of the sample contained one or both 

of these chemicals, with 69.2% of the sample containing 

DA. Both DA and AP were found in 28.3% of the sample 

e‐liquids. These chemicals were detected even in samples 

coming from manufacturers that stated these flavorings 

were not present in their products. However, exposure 

to DA and AP was 100 and 10 times lower, respectively, 

than exposure to these chemicals from cigarette smoking. 

Few studies have examined safe levels of DA and AP via 

tobacco product; however, 47.3% of DA‐ and 41.5%  of 

AP‐containing samples exposed consumers to levels higher 

than the safety limits outlined by the National Institute 

for Occupational Safety (NIOSH) for occupational expo‐

sure. This exposure threshold outlined by NIOSH is not 

intended to suggest exposure at or below that limit should 

be considered sufficiently safe (Hubbs et al. 2015).

Aerosolized Adulterants

TSNAs, potent carcinogens identified in tobacco 

and tobacco smoke, include N‐nitrosonornicotine (NNN), 

4‐(methylnitrosamino)‐1‐(3‐pyridyl)‐1‐butanone (NNK), 

N‐nitrosoanabasine (NAB), and N‐nitrosoanatabine 

(NAT) (Hecht 1998, 1999; USDHHS 2010, 2014). NNN 

and NNK are classified by the International Agency for 

Research on Cancer (IARC) as Group 1 human carcino‐

gens (IARC 2004). Their presence in e‐liquids is mostly 

attributable to the processes used in extracting nicotine 

from tobacco leaves or the addition of tobacco flavorings 

(Kim and Shin 2013; Cheng 2014). These compounds are 

formed from their alkaloid precursors and from nitrite or 

nitrate, predominantly during tobacco curing, fermen‐

tation, and aging. NNN, NAB, and NAT are formed pri‐

marily from their corresponding secondary amines (nor‐

nicotine, anatabine, and anabasine) in the early stages of 

tobacco curing and processing, while the majority of NNK 

is formed from the tertiary amine nicotine at the later 

stages of tobacco curing and fermentation (Hecht 1998). 

Nitrosation reactions of corresponding amines can occur 

in e‐liquids, especially during inadequate storage or man‐

ufacturing processes; inadequate storage is believed to 

increase the levels of NNN as a consequence of the nitro‐

sation of nornicotine converted from nicotine in liquids 

(Kim and Shin 2013).

Some studies have identified traces of TSNAs in 

e‐liquids, but at levels far below those seen in combustible 

tobacco (Trehy et al. 2011; Farsalinos et al. 2015a). Further, 

Goniewicz and colleagues (2014b) found that the aerosol of 

some e‐cigarettes contains traces of the carcinogenic nitro‐

samines NNN and NNK, but neither was detected in aerosol 

from the Nicorette inhalator (an NRT product).
Health Effects of E-Cigarette Use Among U.S. Youth and Young Adults 117

E-Cigarette Use Among Youth and Young Adults

Several studies have reported the presence of other 

hazardous compounds in e‐liquids or in the aerosol pro‐

duced by e‐cigarettes (Exponent Inc. 2009; Hadwiger et al. 

2010; Lim and Shin 2013; Uchiyama et al. 2013; Williams 

et  al. 2013; Bekki et  al. 2014; Goniewicz et  al. 2014a,b; 

Kosmider et al. 2014; Jensen et al. 2015; Kavvalakis et al. 

2015; Laugesen 2015; Oh and Shin 2015; Varlet et al. 2015; 

Khlystov and Samburova 2016). For example, an FDA study 

detected the presence of amino‐tadalafil and rimonabant in 

e‐liquids (Hadwiger et al. 2010); amino‐tadalafil is a struc‐

tural analogue of tadalafil, the active pharmaceutical ingre‐

dient in Cialis, a prescription drug approved in the United 

States for treatment of erectile dysfunction. Rimonabant 

(trade name Zimulti) was approved in Europe for the treat‐

ment of obesity, but its marketing authorization was with‐

drawn by the European Medicines Agency in 2009. FDA 

approval of this drug has been withheld because of unre‐

solved issues involving rimonabant therapy and increased 

frequencies of psychiatric adverse events, including suicide 

and an ill‐defined constellation of neurologic symptoms 

and seizures (FDA 2007). The presence of unapproved active 

pharmaceutical ingredients suggests that some e‐cigarettes 

may expose users to pharmacologically active substances 

with undocumented and unknown effects.

Oh and Shin (2015) conducted a study to identify 

and quantify the presence of diethyl phthalate (DEP) and 

diethylhexyl phthalate (DEHP) in e‐liquids. DEP is used 

as a solvent to bind cosmetics and fragrances and in var‐

ious industrial applications, including plasticizers, deter‐

gent bases, and aerosol sprays. DEHP is used widely as a 

plasticizer in the manufacture of articles made of poly‐

vinylchloride. DEP and DEHP were detected in 47.6% and 

79.1% of e‐liquids, respectively, with concentration 

ranges of 0.01–1745.20 mg/L and 0.06–81.89 mg/L (Oh 

and Shin 2015). Both DEP and DEHP have estrogenic 

and antiandrogenic activity that cause premature breast 

development in girls. DEHP is classified by IARC as a pos‐

sible carcinogen in humans (IARC 2000). Although the 

amounts of the two phthalates detected in this study were 

lower than the safety levels, the source of these toxicants 

is unknown, perhaps coming from packaging materials 

and the production procedure.

Carbonyls are present in e‐cigarettes, and levels 

increase with device voltage (Kosmider et  al. 2014; 

Jensen et al. 2015). Long‐term exposure to carbonyl 

compounds, such as formaldehyde, acetaldehyde, and 

acrolein, increases the risk of cancer. IARC and the U.S. 

Environmental Protection Agency (EPA) have classified 

formaldehyde as “carcinogenic to humans” (USDHHS 

1999; IARC 2009). EPA has set the acceptable daily intake 

(ADI) of formaldehyde as 0.2 mg/kg (kilograms) body 

weight and has warned of the potential adverse health 

effects of exceeding ADI. Acetaldehyde is also toxic, an 

irritant, and a probable carcinogen (USDHHS 1999). 

Acrolein is toxic through all routes of administration and 

may cause respiratory and ocular irritation (Faroon et al. 

2008; Bein and Leikauf 2011). Acrolein in cigarette smoke 

has been linked to several pulmonary diseases, including 

increased risk of lung cancer (Feng et al. 2006), as well 

as asthma and chronic obstructive pulmonary disease 

(Bein and Leikauf 2011). One study found an association 

between acrolein exposure and risk of cardiovascular dis‐

ease (DeJarnett et al. 2014).

Lim and Shin (2013) detected formaldehyde and 

acetaldehyde in 225 replacement liquids for e‐cigarettes 

purchased in Korea, with ranges of 0.02–10.09 mg/L (mean 

2.16 mg/L) and 0.10–15.63 mg/L (mean = 4.98 mg/L). 

Although the amounts of formaldehyde and acetalde‐

hyde detected in replacement liquids for e‐cigarettes are 

relatively low compared to conventional cigarettes, they 

should be controlled to the lowest possible concentrations 

in raw materials, as they may be formed when e‐liquids 

are heated. Furthermore, as larger capacity batteries 

and heating mechanisms are developed (Farsalinos et al. 

2014b; Sleiman et al. 2016), users will be exposed to higher 

concentrations of formaldehyde, acetaldehyde, acro‐

lein, and other carbonyls (Kosmider et al. 2014). Jensen 

and colleagues (2015) reported formaldehyde concentra‐

tions higher than conventional cigarettes in high‐voltage 

e‐cigarettes. Havel and colleagues (2016) reported acetal‐

dehyde, acrolein, and formaldehyde generation increased 

markedly at voltages at or above 5 volts. Geiss and col‐

leagues (2016) reported that formaldehyde exceeded safety 

levels at the lowest wattage (5 watts), which is the wattage 

applied in most second generation e‐cigarettes.

Summary

Although some typical constituents of the e‐cigarette 

aerosol have been identified, the potential short‐ and long‐

term health consequences of inhalation of the heated and 

aerosolized constituents of the e‐liquids, including solvents, 

flavorants, and toxicants, still require further investigation 

to quantify health effects. Commercial and custom‐mixed 

e‐liquids are produced with undisclosed manufacturing 

procedures, packaging materials, and purity standards for 

their constituents, increasing the risks of potential health 

consequences. E‐cigarettes are a source of extremely high 

doses of fine particles (e.g., aerosol) in the human respira‐

tory system. Fine particles are emitted when the solvents 

PG and VG are aerosolized, and mild respiratory effects have 

been documented, but adequate assessments are lacking. 

An additional concern is the aerosolization and inhalation 

of flavor additives in e‐liquids. While some of the chemicals 

used may be generally recognized as safe for use in foods, 

they have not been thoroughly tested for their potential 
A Report of the Surgeon General

118 Chapter 3

sensitizing, toxic, or irritating characteristics when inhaled. 

Further, given the extent of possible variations in the ratio 

of flavor additives, with up to 7,700 unique e‐liquid vari‐

eties available (Zhu et al. 2014b), these chemicals may be 

toxic in the concentrations present in manufactured or 

do‐it‐yourself e‐liquids. Finally, other hazardous com‐

pounds and carcinogens have been detected in e‐liquids, or 

in the heated aerosol produced by e‐cigarettes, including 

formaldehyde, acetaldehyde, and acrolein.

Effects of Toxicants Produced 

During Aerosolization

A primary reason for investigating the health effects 

of heated and aerosolized e‐liquids is that, under such con‐

ditions, chemical reactions may result in the formation of 

new compounds (Sleiman et al. 2016). In some devices, 

the temperature in the center of a heating coil can exceed 

350°C, causing changes in the chemical components of 

the e‐liquid. When carbonyl compounds are present in the 

refill liquids, heating can enhance their concentrations in 

the aerosol (Talih et al. 2015). Carbonyl compounds result 

from dehydration and fragmentation of VG and PG, which 

can be oxidized to formaldehyde and acetaldehyde during 

heating. Hutzler and colleagues (2014) applied headspace 

gas chromatography‐mass spectrometry to enable incuba‐

tion of liquids at various temperatures. At 150°C, the levels 

of acetaldehyde and formaldehyde were found to be up to 

10‐fold higher than they were at ambient temperatures for 

samples in which PG was a main component. The gen‐

eration of carbonyl compounds seems to increase when 

liquids touch the heating element inside an e‐cigarette, 

which is indicated by a color change around the wire, as 

has been reported in some devices (Uchiyama et al. 2013). 

Evidence suggests when e‐liquid touches the heating ele‐

ment (heated nichrome wire), it is oxidized to formalde‐

hyde, acetaldehyde, acrolein, glyoxal, and methylglyoxal 

in the presence of oxygen (Bekki et al. 2014; Goniewicz 

et al. 2014b; Kosmider et al. 2014).

Several studies have reported that short‐chain alde‐

hydes, such as formaldehyde, acetaldehyde, or acrolein, are 

produced during heating. Uchiyama and colleagues (2013) 

measured carbonyl compounds in e‐cigarette aerosols 

generated according to the Canadian “intense regimen” 

(55mL puff volume, 2‐second puff duration, 30  seconds 

between puffs, and a total of 10 puffs). Thirteen brands of 

e‐cigarettes were assessed, and investigators detected sev‐

eral carbonyl compounds, such as formaldehyde, acetal‐

dehyde, acetone, acrolein, propanol, crotonaldehyde, and 

butanol. They also detected two other harmful carbonyl 

compounds that had not been detected in the mainstream 

smoke from conventional cigarettes: glyoxal and methyl‐

glyoxal. Jensen and colleagues (2015) observed that form‐

aldehyde‐containing hemiacetals can be formed during 

the aerosolization process. These molecules are known to 

release formaldehyde and are used as industrial biocides, 

but it is not currently known how formaldehyde‐releasing 

agents affect the respiratory tract.

The amount of carbonyl compounds in e‐cigarette 

aerosols varies substantially, not only among different 

brands but also among different samples of the same prod‐

ucts (Ohta et al. 2011; Bekki et al. 2014; Kosmider et al. 

2014; Jensen et al. 2015), from 100‐fold less than tobacco 

to nearly equivalent values. Notably, the amount of voltage 

the battery puts out affects the concentration of the car‐

bonyl compounds in the emission. Some e‐cigarettes allow 

users to increase aerosol production and nicotine delivery 

by raising the battery’s output voltage. In addition, some 

users elect to directly drip e‐liquid onto an exposed heater 

coil, reportedly for greater aerosol production and “throat 

hit.” Talih and colleagues (2015) showed that use of such 

direct‐drip atomizers may involve greater exposure to 

toxic carbonyls, including formaldehyde, because of the 

potentially higher temperatures reached by the coil. The 

adverse effects of acrolein (2‐propenal), an unsaturated 

aldehyde, depend on dose and cell type and are influenced 

by experimental conditions (Bein and Leikauf 2011). In 

vitro studies found that acrolein inhibits DNA repair and 

forms acrolein‐deoxyguanosine DNA adducts that are 

mutagenic (Wang et  al. 2009, 2012; Tang et  al. 2011). 

Despite the known DNA‐damaging effects of acrolein, its 

mutagenicity in mammalian cells remains uncertain, and 

according to an evaluation by the IARC, there is inade‐

quate evidence for carcinogenicity in humans or animals 

(IARC 1995). Because of its extreme toxicity, acrolein has 

been difficult to characterize in standard animal carcino‐

genicity tests. Animal experiments showed that acrolein 

can have a range of adverse effects, including a role in car‐

cinogenesis (Cohen et al. 1992); excessive mucus produc‐

tion and macrophage and neutrophil accumulation with 

consequent production of proinflammatory cytokines and 

proteases (Moretto et  al. 2012); damage to neurons and 

myelin disruption (Shi et al. 2011); and it may play a role 

in the progression of atherosclerosis and cardiovascular 

disease (Park and Taniguchi 2008; DeJarnett et al. 2014).

Other volatile organic compounds (VOCs) found 

in e‐cigarette aerosol include a variety of chemicals 

(e.g., aliphatic and aromatic hydrocarbons), some of 

which may have short‐ or long‐term adverse health 

effects. Benzene (classified as group 1 by IARC) and other 

solvents (toluene, xylenes, and styrene) could be present 

in e‐cigarettes because of their use in the extraction of 

nicotine from tobacco leaves. Goniewicz and colleagues 

(2014b) detected both toluene and m‐ and p‐xylene in 
Health Effects of E-Cigarette Use Among U.S. Youth and Young Adults 119

E-Cigarette Use Among Youth and Young Adults

e‐cigarette aerosols. A wide variety of other VOCs in 

e‐cigarette liquids produce aromas and flavor through 

heating (Tierney et al. 2016).

Heavy metals such as tin, lead, and nickel were dis‐

covered by Williams and colleagues (2013) in a brand of 

e‐liquids and the resulting aerosols. Those researchers 

analyzed the contents of e‐cigarette cartomizers (a poly‐

fill wrapped heating coil capable of longer puff durations 

than an atomizer) and the aerosols by using light and elec‐

tron microscopy, x‐ray microanalysis, particle counting, 

and inductively coupled plasma optical emission spec‐

trometry. The aerosol contained particles >1 μm that were 

composed of tin, silver, iron, nickel, aluminum, and sili‐

cate, and nanoparticles (<100 nm) of tin, chromium, and 

nickel. Small particles composed of various elements (tin, 

other metals, semimetals, and silicates) passed through 

the cartomizer fibers and were present in aerosols. 

These particles likely originated from parts of the device 

(i.e., atomizer/cartomizer) (Williams et al. 2013).

Concentrations of 9 of the 11 elements in e‐cigarette 

aerosol identified by Williams and colleagues (2013) 

were higher than or equal to concentrations in conven‐

tional cigarette smoke. Many of the metals identified in 

e‐cigarette aerosol, such as lead and cadmium (Farsalinos 

et al. 2015b), are known to cause respiratory distress and 

disease (Zalups and Ahmad 2003). These metals are pro‐

duced by the aerosolization of e‐liquids (Farsalinos et al. 

2015b) and by flaws in e‐cigarette heating mechanisms 

and poor quality control (Williams et al. 2013; Farsalinos 

et al. 2015b; Mikheev et al. 2016). While these initial anal‐

yses indicate potential exposures, additional measures are 

needed because of challenges in measuring trace levels of 

metals.

Summary

E‐liquids produce chemical reactions that may result 

in the formation of new, harmful compounds. Carcinogens 

(e.g., formaldehyde, acetaldehyde, and acrolein) and toxic 

heavy metals (e.g., lead and cadmium) have been found 

in e‐cigarette aerosols in laboratory tests conducted at 

temperatures within the range of most e‐cigarette prod‐

ucts. These chemicals and metals have been detected in 

e‐liquids and e‐cigarette aerosols, signifying the need for 

further study on the potential short‐ and long‐term health 

ramifications.

A limitation to understanding the health impact 

of chemical reactions is the heterogeneity of e‐cigarette 

devices (e.g., voltage), e‐liquids (e.g., quality, content), 

and use behaviors (e.g., puff duration), as emissions 

may be altered by any combination of these mechanical 

and behavioral differences. Further, it is difficult to fully 

contextualize the carcinogenic emissions of e‐cigarette 

aerosol given the diversity of products currently available, 

as well as those that may become available as the devices 

continue to evolve (Farsalinos et al. 2014b).

Effects Not Involving Inhalation of 

Aerosol by the E‐Cigarette User

Health effects not attributable to direct inhalation 

of e‐cigarette aerosol include explosion or fire associ‐

ated with malfunctioned devices, poisoning through con‐

tact exposure or intentional or unintentional ingestion 

of e‐liquid, and exposure to secondhand aerosol or its 

condensate.

Health Effects Attributable to Explosions and 

Fires Caused by E‐Cigarettes

Most reports of explosions and fires caused by 

e‐cigarettes have appeared in print and online media and 

on televised programs. From August 2009 to March 2014, a 

search of U.S. media by the U.S. Fire Administration (2014) 

found 25 reports of e‐cigarette explosions or fires. These 

data suggest that the number of such events is small when 

compared with the number of e‐cigarette users. Of the 

25 incidents found in the search, 2 caused serious harm, 

and there were no deaths attributable to explosions. In most 

cases, the resulting fires did not spread far from the site of 

the explosion. However, in one case an entire bedroom was 

lost to fire (U.S. Fire Administration 2014). As for explo‐

sions, several have occurred during an e‐cigarette’s use, 

causing severe facial damage or injuries to bodies and hands 

(Brennan 2015; Corona and Marcus 2015; Duranty 2015; 

Fox 5 Digital Team 2015; Goff and Schwartz 2015; Jablow 

and Sexton 2015; Shastry and Langdorf 2016), but most 

occurred while the device’s batteries were being charged. 

Overcharging lithium batteries can lead to thermal run‐

away, causing the e‐cigarette battery or container to be 

propelled, often with portions catching fire (U.S. Fire 

Administration 2014; Bohr et al. in press).

Health Effects Caused by Ingestion of E‐Cigarette 

Liquids

The liquids in both e‐cigarettes and the con‐

tainers used to refill them can cause nicotine poisoning. 

Consequences of nicotine intoxication in the e‐liquid 

include nausea, vomiting, headaches, dizziness, and diar‐

rhea at low doses; seizures; tachycardia; abdominal pain; 

confusion; and even death (Cervellin et  al. 2013). The 

amount of nicotine needed to cause death in humans is 

uncertain and, according to a reevaluation, may be higher 

than previously thought (Mayer 2014). The total amount 
A Report of the Surgeon General

120 Chapter 3

of nicotine in refill liquids varies and can be as high as 

1,000 mg/10 mL in do‐it‐yourself bottles (Davis et  al. 

2015), which could be lethal if consumed (Mayer 2014).

The increase in poisonings prompted enactment of 

the Child Nicotine Poisoning Prevention Act of 2015 (2016) 

in January 2016. This law requires any container of liquid 

nicotine sold, manufactured, distributed, or imported 

into the United States be placed in special packaging 

that is difficult to open by children under 5 years of age. 

Although labels may indicate the concentrations of nico‐

tine, such labels can be incomplete, confusing, or inaccu‐

rate (Trtchounian and Talbot 2011; Cameron et al. 2014), 

and some bottles have not been labeled at all (Davis et al. 

2015). Of most concern, some bottles of e‐cigarette refill 

liquids labeled “no nicotine” have been found to contain 

significant amounts of that substance (e.g., 25.6 mg/mL; 

Trehy et al. 2011). Regardless, many e‐cigarette users may 

not be aware of the toxic effects of nicotine and may not 

know that refill liquids should be kept away from toddlers 

and children. These liquids are often sold in colorful bot‐

tles with flavors that are attractive to children (Bahl et al. 

2012). The liquids usually come in small dropper bottles 

that can be mistaken for bottles containing food dye or eye 

drops. Finally, many refill liquids are made in local “vape 

shops,” which have only recently come under FDA regu‐

lation (Federal Register 2016), with no uniform training 

process for mixers, a lack of standards and protections, 

and unknown concentrations of nicotine.

The rapid growth in popularity of e‐cigarettes and 

the ease with which refill liquids can be purchased have 

made e‐cigarettes an increasingly common item in many 

households, thereby elevating the possibility of accidental 

nicotine poisoning. Instances of related case reports, often 

involving children or infants, are increasing. For example, 

an 18‐month‐old girl was treated at an emergency room 

for hypertension and tachycardia after drinking about 

2 mL of refill liquid from a bottle on a nightstand (Shawn 

and Nelson 2013). Unintentional exposure to nicotine 

can occur through ingestion, absorption through the 

skin, inhalation, or dropping refill liquids into one’s eyes 

(Cantrell 2014).

Figure 3.2 shows data from 2011 to 2016 on expo‐

sures to e‐cigarettes or liquid nicotine (i.e., any con‐

tact with e‐cigarettes or liquid nicotine, not necessarily 

resulting in any health effects) (American Association of 

Poison Control Centers 2016). These data show a dramatic 

increase in exposures through 2014 with a slight reduc‐

tion of exposures in 2015. Fifty‐one percent of the calls to 

poison control centers regarding exposures to e‐cigarettes 

involved children 5 years of age or younger (CDC 2014). 

Increased e‐cigarette exposures have also been reported by 

state and local poison centers (Banerji et al. 2014; Cantrell 

2014; Guttenburg et al. 2014; Lee et al. 2014; California 

Department of Public Health 2015).

Secondhand Exposure to the 

Constituents of E‐Cigarette Aerosol 

Exposure to secondhand smoke from combustible 

tobacco products is a known cause of morbidity and mor‐

tality (USDHHS 2006). Secondhand smoke, a mixture of 

the sidestream smoke from a smoldering cigarette and the 

mainstream smoke exhaled by a smoker, is known to con‐

taminate both indoor and outdoor environments. In addi‐

tion, when the constituents of smoke deposit on surfaces, 

nonsmokers can be exposed to them via touch, ingestion, 

or inhalation. These deposited constituents of combustible 

smoke are known as “thirdhand smoke” (Matt et al. 2011; 

Protano and Vitali 2011). E‐cigarettes represent another 

potential source of exposure to toxicants for nonusers, via 

secondhand or thirdhand exposure to aerosol.

Exposure to Nonusers

In contrast to combustible tobacco products, 

e‐cigarettes do not produce sidestream emissions; aerosol 

is produced during activation of the device. Some of this 

aerosol is subsequently exhaled into the environment 

where nonusers may be exposed through inhalation, inges‐

tion, or dermal contact. As previously described in this 

chapter, constituents of the emissions may include nico‐

tine, carbonyl compounds, VOCs, polyaromatic hydro‐

carbons, TSNAs, heavy metals, and glycols. It is not clear 

how much of inhaled e‐cigarette aerosol is exhaled into 

the environment where nonusers can be exposed. Some 

studies have used machines to produce e‐cigarette aero‐

sols and measured the pollutants emitted (McAuley et al. 

2012; Czogala et al. 2014; Geiss et al. 2015); others have 

involved the use by one or more persons of an e‐cigarette 

and measured the change in pollutants in either a room 

or a test chamber after use (Schripp et al. 2013; Schober 

et al. 2014). One study measured airborne nicotine in the 

homes of e‐cigarette users (Ballbe et al. 2014). The concen‐

tration of e‐cigarette aerosol in a given microenvironment 

depends primarily on the strength of the source or the 

number of e‐cigarettes used and the emission rate of the 

aerosol for that device. E‐cigarettes, however, are heteroge‐

neous in their design and in the liquids used, and the spe‐

cific product combination significantly affects the second‐

hand emissions (Kosmider et al. 2014; Geiss et al. 2015). 

The number of puffs and depth of inhalation may be partic‐

ularly relevant to the amount exhaled by the user and may 

also affect e‐cigarette emissions (Talih et al. 2016).
Health Effects of E-Cigarette Use Among U.S. Youth and Young Adults 121

E-Cigarette Use Among Youth and Young Adults

Figure 3.2 Data showing exponential increase in the number of cases of human exposure to e‐cigarette products and 

liquid nicotine between 2011 and 2016

Source: American Association of Poison Control Centers (2016).

Note: These numbers reflect the closed human exposures to e‐cigarettes and liquid nicotine reported to poison centers as of July 31, 

2016. The numbers may change as cases are closed and additional information is received.

Movement of E‐Cigarette Aerosol

Similar to the case with secondhand tobacco smoke, 

e‐cigarette aerosol is an inherently dynamic mixture that 

changes over time in terms of constituents and concen‐

trations. Czogala and colleagues (2014) demonstrated a 

significant signal from a laser photometer indicating the 

presence of ambient aerosol in a room after e‐cigarette 

use. However, this aerosol disappeared in just seconds 

to a few minutes as it either evaporated to the gas phase 

or deposited on surfaces in the room. In contrast, in the 

same study, secondhand cigarette smoke exhibited a par‐

ticulate phase that stayed suspended in the room at high 

concentrations for more than 30 minutes. For the VOCs 

in e‐cigarette aerosol, such as formaldehyde, acrolein, and 

acetaldehyde, the source strength and ventilation rate will 

largely determine their concentration in indoor air. Semi‐

VOCs, such as nicotine and TSNAs, are also largely affected 

by sorption on and subsequent desorption from surfaces 

and dust in a room (Singer et al. 2002, 2003; Goniewicz 

and Lee 2015). The extent of this type of thirdhand con‐

tamination from e‐cigarettes in real‐world settings has 

not been established but would be of particular concern 

for children living in homes of e‐cigarette users, as they 

spend more time indoors, are in proximity to and engage 

in greater activity in areas where dust collects and may be 

resuspended (e.g., carpets on the floor), and insert non‐

food items in their mouths more frequently (EPA 2008; 

Matt et al. 2011).

Exposure to E‐Cigarette Aerosol and 

Considerations of Dose

A large body of studies has measured exposure to 

secondhand and thirdhand smoke from conventional 

cigarettes using personal or area air monitoring, sur‐

face testing, and dust testing. Studies of the exposure 

of e‐cigarette aerosol to nonusers, however, are limited. 

Schripp and colleagues (2013) observed small increases of 

fine and ultrafine particles and some VOCs, including PG, 
A Report of the Surgeon General

122 Chapter 3

flavoring substances, and nicotine, indicating passive inha‐

lation of e‐cigarette aerosols by nonusers in the presence 

of e‐cigarette users. Those authors demonstrated that the 

distribution in the sizes of the aerosol’s component par‐

ticles changes in the lungs and results in the exhalation of 

smaller particles, likely caused by the evaporation of the 

liquid particles in the lungs and in the environment after 

exhalation. Schober and colleagues (2014) found substan‐

tially higher amounts of PG, VG, particulate matter (PM), 

and nicotine in a 45‐m3 chamber during e‐cigarette use 

sessions with volunteers compared to controlled sessions. 

They also found a 20% increase in the level of polycyclic 

aromatic hydrocarbons (PAHs) and a 2.4‐fold increase in 

aluminum concentrations.

Williams and colleagues (2013) demonstrated con‐

tamination by metal and silicate particles in e‐liquid 

and its aerosol using scanning electron microscopy. In 

a different study measuring machine‐generated second‐

hand e‐cigarette aerosol in an emission chamber, Geiss 

and colleagues (2015) found significant levels of PG, VG, 

and nicotine in the chamber’s air. Carbonyl compounds 

of concern (e.g., formaldehyde, acetaldehyde, acrolein, 

and acetone) were below the limits of detection in this 

study. O’Connell and colleagues (2015), who assessed 

secondhand e‐cigarette emissions in a small meeting 

room (12.8  m2) with three e‐cigarette users during a 

165‐minute session, found a significant increase in PG but 

did not see the expected increase in VG or nicotine. This 

study reported no increase in PAHs, trace metals, TSNAs, 

or acrolein, but did find an increase in total VOCs, formal‐

dehyde, and acetaldehyde. However, the compounds were 

found at levels below guidelines for the quality of indoor 

air from the World Health Organization or European 

Union. Ruprecht and colleagues (2014) found signifi‐

cantly lower concentrations and counts for particles from 

an e‐cigarette used in a 50‐m3 room compared with con‐

ventional cigarettes. Interestingly, they also found that 

nicotine‐free e‐cigarettes produced higher particle levels 

than e‐cigarettes containing nicotine. Saffari and col‐

leagues (2014) found that total particulate exposure was 

10‐fold lower in e‐cigarettes than it was in conventional 

cigarettes. Emissions of heavy metals from e‐cigarettes 

were also dramatically less, with the exception of nickel, 

zinc sulfide, and silver, which showed higher emission 

rates from e‐cigarettes. PAH levels were not elevated by 

e‐cigarette use in this study.

Concentrations of PM, especially PM2.5, which is 

fine PM, and nicotine are the two most common markers 

used to measure exposure to secondhand smoke (Avila‐

Tang et al. 2010; Apelberg et al. 2013). Indirect measures 

of the mass concentration of PM from secondhand smoke 

using real‐time particle monitors are well validated in 

terms of the accuracy of these measurements in relation 

to other constituents of secondhand smoke and to health 

effects (Hyland et  al. 2008; Apelberg et  al. 2013). These 

same types of particle monitors are often used in studies 

of e‐cigarette aerosol to compare PM levels from conven‐

tional cigarettes with those from e‐cigarettes, though PM 

findings may not directly relate to the short‐ and long‐

term health effects of each product (Czogala et al. 2014; 

Schober et al. 2014).

Caution is warranted when interpreting the results 

of PM measurements comparing e‐cigarettes with conven‐

tional cigarettes. The aerosols produced are fundamentally 

different, with the former resulting from aerosolization of 

liquid and the latter resulting from combustion of organic 

matter. The true PM2.5 mass concentration of e‐cigarette 

aerosol from commonly used light‐scattering instruments 

(Czogala et al. 2014) cannot be determined without cali‐

brating the device to a reference standard for the aerosol 

in question. Even this calibration would be questionable 

given the highly volatile nature of e‐cigarette aerosol, 

making it difficult to capture and accurately determine 

the mass. Real‐time PM2.5 measurements such as this are 

useful, however, to determine the presence of an aerosol 

and to see the relative changes in this aerosol over time 

and under various conditions, such as changing source 

strength. Figure 3.3 shows the significant increase in 

aerosol concentration from e‐cigarettes after about 1 hour 

and the subsequent rapid decline, presumably from initial 

aerosolization and deposition of this aerosol. There may 

still be significant amounts of this e‐cigarette aerosol in 

the environment, but the particle monitor can no longer 

measure it, as it is either in the aerosol phase or deposited 

on surfaces. For these reasons, it is important not to rely 

solely on PM mass concentrations for determining expo‐

sure to e‐cigarette aerosol and for making comparisons 

with conventional cigarettes. Measurement of the indi‐

vidual toxicants of concern in the aerosol phase and on 

surfaces is warranted.

Health Effects of Secondhand Exposure to 

E‐Cigarette Aerosols

Flouris and colleagues (2012, 2013) conducted two 

clinical studies of the health effects of secondhand exposure 

to e‐cigarette aerosol. The researchers found no short‐term 

change in markers of complete blood count after 1 hour 

of exposure to e‐cigarette aerosol in a group of 15  non‐

smokers (Flouris et al. 2012). Similarly, the same exposure 

caused no significant change in short‐term lung function, 

although the results were of borderline statistical signifi‐

cance (Flouris et  al. 2013). However, these studies dem‐

onstrated that passive exposure to e‐cigarettes causes an 

increase in serum cotinine that is similar to that from pas‐

sive exposure to cigarette smoke, suggesting the need to 
Health Effects of E-Cigarette Use Among U.S. Youth and Young Adults 123

E-Cigarette Use Among Youth and Young Adults

examine the impact of passive aerosolized nicotine inha‐

lation on long‐term lung function. Furthermore, limited 

effects would likely occur in the short exposure observed 

through the methodologies used by Flouris and colleagues 

(2012, 2013), as these studies did not account for prolonged 

and persistent passive exposure to e‐cigarette aerosols.

Figure 3.3 Changes in aerosol particle PM2.5 concentrations during experiment of e‐cigarette use and tobacco 

cigarette smoking in an exposure chamber

Source: Czogala et al. (2014).

Note: PM = particulate matter.

Several researchers have modeled the health risks 

of passive exposure to e‐cigarettes (Colard et al. 2015) on 

the basis of the limited exposure data available and have 

come to various conclusions. Offermann (2015) concluded 

that, for indirect exposure, two chemicals—nicotine and 

PG—exceeded California EPA exposure level standards for 

noncarcinogenic health effects. Burstyn (2014), who com‐

pared e‐cigarette aerosol exposure to workplace exposure 

standards, concluded that only PG and VG warrant atten‐

tion in e‐cigarette users while, for bystanders, none of the 

constituents of e‐cigarette aerosol pose apparent concern. It 

is important to note that standards for workplace exposure 

are typically not appropriate to apply to the population as a 

whole, as they are intended for a healthy working popula‐

tion during a typical work day, not accounting for the risks 

to children, pregnant women, or those with preexisting 

health conditions. Further, standards for workplace expo‐

sure are very different in concentration and duration than 

what is to be expected from e‐cigarette use.

An additional consideration for regulating e‐cigarettes 

in indoor environments is the potential for allergic reactions 

in nonusers. Dermal and oral PG exposures are known causes 

of dermatitis and allergic sensitization (Warshaw et al. 2009; 

Al Jasser et  al. 2011). Several e‐liquids contain flavorants 

derived from nuts and in fact have labels cautioning persons 

who have nut allergies not to use these products. Research 

has not evaluated whether nonusers can have allergic reac‐

tions from these potential allergens in e‐cigarette aerosol, 

but this is a risk that should be explored as 8% of U.S. chil‐

dren have food allergies (Gupta et al. 2011).
A Report of the Surgeon General

124 Chapter 3

Evidence Summary

E‐cigarette use among youth and young adults in the 

United States has increased considerably in recent years (see 

Chapter 2). There is little doubt that the use of e‐cigarettes 

by youth and young adults represents self‐administration 

of the drug nicotine, and this self‐administration of nic‐

otine puts youth at risk for addiction and many related 

harmful consequences. Animal research indicates adoles‐

cent brains are particularly sensitive to nicotine’s effects, 

such that subsequent self‐administration is more likely, 

and that same literature indicates that this age group is 

at risk for a constellation of nicotine‐induced neural and 

behavioral alterations. Studies of the effects of maternal 

smoking of conventional cigarettes during pregnancy, 

coupled with preclinical literature examining the effects 

of maternal self‐administration of nicotine during preg‐

nancy, suggest that e‐cigarette use by mothers during 

pregnancy presents a wide variety of risks to fetal, infant, 

and child brain development.

Users of e‐cigarettes risk respiratory exposure to a 

variety of aerosolized chemicals, including solvents and fla‐

vorants added intentionally to e‐liquids, adulterants added 

unintentionally, and other toxicants produced during the 

heating/aerosolization process. The health impacts of fre‐

quent exposure to the toxicants in e‐cigarette aerosol 

are not well understood, though several are known car‐

cinogens. As highlighted previously in this chapter, the 

detection and level of these carcinogens depend on several 

factors, including the concentration of the e‐liquid and the 

strength of the heating device. Although e‐cigarettes have 

been used as a cessation device, the evidence supporting the 

effectiveness of e‐cigarettes as an aid for quitting conven‐

tional cigarettes remains extremely weak for adults (Bullen 

et  al. 2013; Caponnetto et  al. 2013; Grana et  al. 2014; 

Kalkhoran and Glantz 2016) and untested and nonexistent 

among youth.

Further research is warranted to focus on the 

characteristics of e‐cigarette devices, the constituents 

of e‐liquids, and the user behaviors that can influence 

the yield of nicotine and other toxicants (Shihadeh and 

Eissenberg 2015). This close focus includes providing 

details of devices (e.g., voltage of the power supply, heating 

element resistance) and components of e‐liquids (e.g., pro‐

pylene glycol, vegetable glycerin, other additives), and 

measuring user puff topography. Standardization of pro‐

cedures for producing and delivering the aerosol is likely a 

necessary component of at least some in vivo and in vitro 

work. Preclinical work examining the effects of e‐cigarette 

aerosols is a clear research need and, again, the standard‐

ization of procedures for production and delivery of the 

aerosol is necessary. To enhance relevance, the parameters 

of aerosol production should span the range of those seen 

with humans (Shihadeh and Eissenberg 2011).

The huge variety of products of different origin and 

design, the rapid emergence of new products, and the 

varied ways in which consumers use these products make 

the development of standard measurement conditions 

challenging (Famele et al. 2015). Accordingly, research is 

needed to understand how different design features relate 

to potential toxicity—for example, if the compounds in 

e‐cigarettes are affected by heating, changes in chemical 

composition, or pH; if these compounds are absorbed into 

the bloodstream; and how additives to the e‐liquid affect 

the bioavailability of these compounds, among other con‐

siderations. Research is also needed to understand whether 

potential health risks may be ameliorated by changes in 

product engineering.
Health Effects of E-Cigarette Use Among U.S. Youth and Young Adults 125

E-Cigarette Use Among Youth and Young Adults

Conclusions

1. Nicotine exposure during adolescence can cause addic‐

tion and can harm the developing adolescent brain.

2. Nicotine can cross the placenta and has known effects 

on fetal and postnatal development. Therefore, nico‐

tine delivered by e‐cigarettes during pregnancy can

result in multiple adverse consequences, including

sudden infant death syndrome, and could result in

altered corpus callosum, deficits in auditory pro‐

cessing, and obesity.

3. E‐cigarettes can expose users to several chemicals,

including nicotine, carbonyl compounds, and vol‐

atile organic compounds, known to have adverse

health effects. The health effects and potentially 

harmful doses of heated and aerosolized constituents 

of e‐cigarette liquids, including solvents, flavorants, 

and toxicants, are not completely understood.

4. E‐cigarette aerosol is not harmless “water vapor,”

although it generally contains fewer toxicants than

combustible tobacco products.

5. Ingestion of e‐cigarette liquids containing nicotine

can cause acute toxicity and possibly death if the

contents of refill cartridges or bottles containing

nicotine are consumed.
A Report of the Surgeon General

126 Chapter 3

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